Fooled By Randomness Nassim Taleb

About the author

N assim Nicholas Taleb is the founder of Empirica Capital LLC, a
crisis-hunting hedge fund operator, and a fellow at the Courant
Institute of Mathematical Sciences of New York University. He has held
a variety of derivative trading positions in New York and London and
worked as an independent floor trader in Chicago. Taleb was inducted
in February 2001 in the Derivatives Strategy Hall of Fame.

Taleb received an MBA from the Wharton School and a Ph.D. from
University Paris-Dauphine. He is the author of Dynamic Hedging:
Managing Vanilla and Exotic Options (Wiley, 1997).

The Hidden Role of Chance
in the Markets and in Life

NASSIM NICHOLAS TALEB

B

TEXE RE

New York • London

Preface and Acknowledgments xiii

Chapter Summaries xvii

Prologue 1

Mosques in the Clouds 1

PART I: Solon’s Warning - Skewness, Asymmetry,

Induction 7

One: If You’re So Rich Why Aren’t You So Smart? 11

Nero Tulip 11

Hit by Lightning 1 1

Temporary Sanity 12

Modus Operandi 14

No Work Ethics 16

There Are Always Secrets 17

John the High-Yield Trader 17

An Overpaid Hick 19

CONTENTS

viii

The Red-Hot Summer 21

Serotonin and Randomness 22

Your Dentist Is Rich, Very Rich - 24

Two: A Bizarre Accounting Method 26

Alternative History 26

Russian Roulette 27

An Even More Vicious Roulette 28

Smooth Peer Relations 29

Salvation Via Aeroflot 30

Solon Visits Regine’s Night Club 32

George Will Is No Solon: On Counterintuitive Truths 34

Humiliated in Debates 37

Risk Managers 38

Three: A Mathematical Meditation on History 40

Europlayboy Mathematics 40

The Tools 41

Monte Carlo Mathematics 43

Fun in My Attic 45

Making History 45

Zorglubs Crowding the Attic 46

Denigration of History 47

The Stove Is Hot 48

My Solon 50

Distilled Thinking on Your PalmPilot 51

Breaking News 51

Shiller Redux 53

Gerontocracy 55

Pbilostratus in Monte Carlo: On the Difference Between Noise

and Information 56

Four: Randomness, Nonsense, and the Scientific Intellectual 60

Randomness and the Verb 60

Reverse Turing Test 62

CONTENTS ix

The Father of All Pseudothinkers 64

Monte Carlo Poetry 64

Five: Survival of the Least Fit - Can Evolution Be Fooled by

Randomness? 68

Carlos the Emerging Markets Wizard 68

The Good Years 71

Averaging Down 72

Lines in the Sand 72

John the High-Yield Trader 74

The Quant Who Knew Computers and Equations 75

The Traits They Shared 78

A Review of Market Fools of Randomness Constants 78

Naive Evolutionary Theories 81

Can Evolution be Fooled by Randomness? 82

Six: Skewness and Asymmetry 84

The Median Is Not the Message 84

Bull and Bear Zoology 86

An Arrogant 29-Year-Old Son 88

Rare Events 89

Symmetry and Science 90

The Rare Event Fallacy 93

The Mother of All Deceptions 93

Why Don’t Statisticians Detect Rare Events? 96

A Mischievous Child Replaces the Black Balls 97

Seven: The Problem of Induction 99

From Bacon to Hume 99

Cygnus Atratus 100

Niederhoffer, Victorian Gentleman 100

Sir Karl’s Promoting Agent 103

Location, Location 105

Popper’s Answer 106

Open Society 108

X

CONTENTS

Nobody Is Perfect 108

Pascal’s Wager 109

Thank You Solon _ 120

PART IP Monkeys on Typewriters - Survivorship and

Other Biases 111

It Depends On the Number of Monkeys 114

Vicious Real Life 115

This Section 115

Eight: Too Many Millionaires Next Door 117

How To Stop the Sting of Failure 117

Somewhat Happy 117

Too Much Work 118

You’re a Failure 119

Double Survivorship Biases 120

More Experts 120

Visibility Winners 122

It’s a Bull Market 122

A Guru’s Opinion 123

Nine: It Is Easier To Buy and Sell Than Fry an Egg 125

Fooled by Numbers 127

Placebo Investors 127

Nobody Has To Be Competent 128

Ergodicity 129

Life Is Coincidental 131

The Mysterious Letter 131

An Interrupted Tennis Game 132

The Birthday Paradox 132

It’s a Small World! 132

Data Mining, Statistics, and Charlatanism 133

The Best Book I Have Ever Read! 134

The Backtester 134

A More Unsettling Extension 136

CONTENTS xi

The Earnings Season: Fooled by the Results 136

Cancer Cures 137

Professor Pearson Goes to Monte Carlo (Literally):

Randomness Does Not Look Random! 139

The Dog That Did Not Bark: On Biases in Scientific

Knowledge 1 40

I Have No Conclusion 141

Ten: Loser Takes All - On the Nonlinearities of Life 142

The Sandpile Effect 142

Enter Randomness 144

Learning to Type 144

Mathematics Inside and Outside the Real World 146

Buridan’s Donkey or the Good Side of Randomness 147

When It Rains, It Pours 148

Eleven: Randomness and Our Brain: We Are Probability

Blind 149

Paris or the Bahamas ? 149

Some Architectural Considerations ISO

From Psychology to Neurobiology 152

Our Natural Habitat 153

Kafka in a Courtroom 154

An Absurd World 156

Kahneman and Tversky 157

Neurobiology 158

Examples of Biases in Understanding Probability 159

We Are Option Blind 160

Probabilities and the Media (More Journalists) 1 62

CNBC at Lunch Time 163

You Should Be Dead by Now 163

The Bloomberg Explanations 164

Filtering Methods 166

We Do Not Understand Confidence Levels 168

An Admission 168

CONTENTS

xii

PART IIP Wax in my Ears - Living With Randomitis 169

I Am Not So Intelligent _ 172

The Odyssean Mute Command 1 73

Twelve: Gamblers’ Ticks and Pigeons in a Box 175

Taxi-Cab English and Causality 175

The Skinner Pigeon Experiment 178

Philostratus Redux 179

Thirteen: Carneades Comes to Rome: On Probability and

Skepticism 182

Carneades Comes to Rome 183

Probability the Child of Skepticism 184

Monsieur de Norpois’s Opinions 185

Path Dependence of Beliefs 187

Computing Instead of Thinking 188

From Funeral to Funeral 190

Fourteen: Bacchus Abandons Antony 191

Notes on Jackie O.’s Funeral 192

Randomness and Personal Elegance 194

Epilogue: Solon Told You So 196

Beware the London Traffic Jams 196

Notes 197

Index 198

About TEXERE 204

T his book is the synthesis of, on one hand, the no-nonsense
mathematical trader (self-styled “practitioner of uncertainty”) who
spent his life trying to resist being fooled by randomness and trick the
emotions associated with uncertainty and, on the other, the aesthetically
obsessed, literature-loving human being willing to be fooled by any form
of nonsense that is polished, refined, original, and tasteful. I am not
capable of avoiding being the fool of randomness; what I can do is
confine it to where it brings some aesthetic gratification.

Much has been written about our biases (acquired or genetic) in
dealing with randomness over the past decade. My rules while writing
this book have been to avoid discussing (a) anything that I did not either
personally witness on the topic or develop independently, and (b)
anything that I have not distilled well enough to be able to write on the
subject with the slightest effort. Everything that remotely felt like work
was out. I had to purge the text from passages that seemed to come from
a visit to the library, including the scientific name dropping. I tried to
use no quote that does not naturally spring from my memory and does
not come from a writer whom I have intimately frequented over the
years (I detest the practice of random use of borrowed wisdom - much
on that, later). Aut tace aut loquere meliora silencio (only when the
words outperform silence).

XIV

PREFACE AND ACKNOWLEDGMENTS

I tried to make the minimum out of my direct profession of
mathematical trader. Markets are a mere special case of randomness
traps. I discuss them in an illustrative way as I would jn a dinner
conversation with, say, a cardiologist with intellectual curiosity (I used
as a model my second-generation friend Jacques Merab).

Some acknowledgments: first, I would like to thank friends who can
be considered rightful co-authors. I am grateful to New York intellectual
and expert in randomness Stan Jonas (I do not know any other
designation that would do him justice) for half a lifetime of conversations
into all subjects bordering on probability with the animation and the zeal
of the neophyte. I thank my probabilist friend Don Geman (husband of
Helyette Geman, my thesis director) for his enthusiastic support for my
book; he also made me realize that proba bilists are born, not made -
many mathematicians are capable of computing, but not understanding,
probability (they are no better than the general population in exerting
probabilistic judgments). The real book started with an all-night
conversation with my erudite friend Jamil Baz during the summer of
1987, as he discussed the formation of “new” and “old” money among
families. I was then a budding trader and he scorned the arrogant
Salomon Brothers traders that surrounded him (he was proved right). He
instilled in me the voracious introspection about my performance in life
and really gave me the idea for this book. Both of us ended up getting
doctorates later in life, on an almost identical subject matter. I have also
dragged many people on (very long) walks in New York, London, or
Paris, discussing some parts of this book, such as the late Jimmy Powers,
who helped nurture my trading early on, and who kept repeating
“anyone can buy and sell”, or my encyclopedic friend David Pastel
equally at ease with literature, mathematics, and Semitic languages. I
have also engaged my lucid Popperian colleague Jonathan Waxman in
numerous conversations on the integration of Karl Popper’s ideas in our
life as traders.

Second, I have been lucky to meet Myles Thompson and David
Wilson, when they both were at J. Wiley 6c Sons. Myles has vision - he
is the reverse “me too” publisher. He understands that books need not
be written to satisfy a pre-defined labeled audience, but that a book will
find its own unique set of readers - thus giving more credit to the reader
than the off-the-rack publisher. As to David, he believed enough in the

PREFACE AND ACKNOWLEDGMENTS

xv

book to push me to take it into its natural course, free of all labels and
taxonomies. David saw me the way I view myself; someone who has a
passion for probability and randomness, who is obsessed with literature
but happens to be a trader, rather than a generic “expert”. He also saved
my idiosyncratic style from the dulling of the editing process (for all its
faults, the style is mine). Finally, Mina Samuels proved to be the greatest
conceivable editor: immensely intuitive, cultured, aesthetically
concerned, yet nonintrusive.

Many friends have fed me with ideas during conversations, ideas that
found their way into the text. I can mention the usual suspects, all of
them prime conversationalists: Cynthia Shelton Taleb, Helyette Geman,
Marie-Christine Riachi, Paul Wilmott, Shaiy Pilpel, David DeRosa, Eric
Briys, Sid Kahn, Jim Gatheral, Bernard Oppetit, Cyrus Pirasteh, Martin
Mayer, Bruno Dupire, Raphael Douady, Marco Avellaneda, Didier
Javice, Neil Chriss, and Philippe Asseily.

Some of these chapters were composed and discussed as part of the
“Odeon Circle”, as my friends and I met with a varying degree of
regularity (on Wednesdays at 10 p.m. after my Courant class) at the bar
of the restaurant Odeon in Tribecca. Genius loci (“the spirit of the
place”) and outstanding Odeon staff member Tarek Khelifi made sure
that we were well taken care of and enforced our assiduity by making
me feel guilty on no-shows, thus helping greatly with the elaboration of
the book. We owe him a lot.

I must also acknowledge the people who read the MS, diligently
helped with the errors, or contributed to the elaboration of the book
with useful comments: Inge Ivchenko, Danny Tosto, Manos
Vourkoutiotis, Stan Metelits, Jack Rabinowitz, Silverio Foresi, Achilles
Venetoulias, and Nicholas Stephanou. Erik Stettler was invaluable in his
role as a shadow copy editor. All mistakes are mine.

Finally, many versions of this book sat on the web, yielding sporadic
(and random) bursts of letters of encouragement, corrections, and
valuable questions which made me weave answers into the text. Many
chapters of this book came in response to readers’ questions. Francesco
Corielli from Bocconi alerted me on the biases in the dissemination of
scientific results.

This book was written and finished after I founded Empirica, my
intellectual home, “Camp Empirica”, in the woods in the back country

XVI

PREFACE AND ACKNOWLEDGMENTS

of Greenwich, CT, which I designed to fit my taste and feel like a hobby;
a combination of an applied probability research laboratory, athletic
summer camp, and, not least, a crisis hunting hedge fund operation (I
had experienced one of my best professional years while writing these
lines). I thank all the like-minded people who helped fuel the stimulating
atmosphere there: Pallop Angsupun, Danny Tosto, Peter Halle, Mark
Spitznagel, Yuzhang Zhou, and Cyril de Lambilly as well as the
members of Paloma Partners such as Tom Witz who challenged our
wisdom on a daily basis or Donald Sussman who supplied me with his
penetrating judgment.

One: If You’re So Rich Why Aren’t You So Smart?

An illustration of the effect of randomness on social pecking order and jealousy,
through two characters of opposite attitudes. On the concealed rare event. How
things in modern life may change rather rapidly, except, perhaps, in dentistry.

Two: A Bizarre Accounting Method

On alternative histories, a probabilistic view of the world, intellectual fraud, and the
randomness wisdom of a Frenchman with steady bathing habits. How journalists
are bred to not understand random series of events. Beware borrowed wisdom: how
almost all great ideas concerning random outcomes are against conventional
sapience. On the difference between correctness and intelligibility.

Three: A Mathematical Meditation on History

On Monte Carlo simulation as a metaphor to understanding a sequence of random
historical events. On randomness and artificial history. Age is beauty, almost
always, and the new and the young are generally toxic. Send your history professor
to an introductory class on sampling theory.

Four: Randomness, Nonsense, and the Scientific Intellectual

On extending the Monte Carlo generator to produce artificial thinking and compare
it with rigorous non-random constructs. The science wars enter the business world.
Why the aesthete in me loves to be fooled by randomness.

CHAPTER SUMMARIES

xviii

Five: Survival of the Least Fit - Can Evolution Be Fooled by
Randomness?

A case study on two rare events. On rare events and evolution. HowJ‘Darwinism”
and evolution are concepts that are misunderstood in the non-biological world. Life
is not continuous. How evolution will be fooled by randomness. A preparation to
the problem of induction.

Six: Skewness and Asymmetry

We introduce the concept of skewness: why the terms “bull” and “bear” have limited
meaning outside of zoology. A vicious child wrecks the structure of randomness. An
introduction to the problem of epistemological opacity. The penultimate step before
the problem of induction.

Seven: The Problem of Induction

On the chromodynamics of swans. Taking Solon’s warning into some philosophical
territory. How Victor Niederhoffer taught me empiricism; I added deduction. Why
it is not scientific to take science seriously. Soros promotes Popper. That bookstore
on 21st and Fifth Avenue. Pascal’s wager.

Eight: Too Many Millionaires Next Door

Three illustrations of the survivorship bias. Why very few people should live on Park
Avenue. The millionaire next door has very flimsy clothes. An overcrowding of
experts.

Nine: It Is Easier To Buy and Sell Than Fry an Egg

Some technical extensions of the survivorship bias. On the distribution of “coin-
cidences” in life. It is preferable to be lucky than competent (but you can be caught).
The birthday paradox. More charlatans (and more journalists). How the researcher
with work ethics can find just about anything in data. On dogs not barking.

Ten: Loser Takes All - On the Nonlinearities of Life

The nonlinear viciousness of life. Moving to Bel Air and acquiring the vices of the
rich and famous. Why Microsoft’s Bill Gates may not be the best in his business (but
please do not inform him of such a fact). Depriving donkeys of food.

Eleven: Randomness and Our Brain: We Are Probability Blind

On the difficulty of thinking of your vacation as a linear combination of Paris and
the Bahamas. Nero Tulip may never ski in the Alps again. Some discussion of
behavioral discoveries. Some manifestations of probability blindness taken out of a
textbook. A little more on journalistic pollution. Why you may be dead by now.

CHAPTER SUMMARIES

XIX

Twelve: Gamblers’ Ticks and Pigeons in a Box

On gamblers’ ticks crowding up my life. Why bad taxi-cab English can help you
make money. How I am the fool of all fools, except that I am aware of it. Dealing
with my genetic unfitness. No boxes of chocolate under my trading desk.

Thirteen: Carneades Comes to Rome: On Probability and Skepticism

Cato the censor sends Carneades packing. Monsieur de Norpois does not remember
his old opinions. Beware the scientist. Marrying ideas. The same Robert Merton
helping the author start his firm. Science evolves from funeral to funeral.

Fourteen: Bacchus Abandons Antony

Montherlant’s death. Stoicism is not the stiff upper lip, but the illusion of victory of
man against randomness. It is so easy to be heroic. Randomness and personal
elegance.

Mosques in the Clouds

T his book is about luck disguised and perceived as non-luck (that is,
skills) and, more generally, randomness disguised and perceived as
non-randomness (that is, determinism). It manifests itself in the shape of
the lucky fool, defined as a person who benefited from a dispropor-
tionate share of luck but attributes his success to some other, generally
very precise, reason. Such confusion crops up in the most unexpected
areas, even science, though not in such an accentuated and obvious
manner as it does in the world of business. It is endemic in politics, as it
can be encountered in the shape of a country’s president discoursing on
the jobs that “he” created, “his” recovery, and “his predecessor’s”
inflation.

We are genetically still very close to our ancestors who roamed the
savannah. The formation of our beliefs is fraught with superstitions -
even today (I might say, especially today). Just as one day some
primitive tribesman scratched his nose, saw rain falling, and developed
an elaborate method of scratching his nose to bring on the much-needed
rain, we link economic prosperity to some rate cut by the Federal
Reserve Board, or the success of a company with the appointment of the
new president “at the helm”. Bookstores are full of biographies of
successful men and women presenting their specific explanation on how
they made it big in life (we have an expression, “the right time and the
right place” to weaken whatever conclusion can be inferred from them).

2

PROLOGUE

This confusion strikes people of different persuasions; the literature
professor invests a deep meaning into a mere coincidental occurrence of
word patterns, while the financial statistician proudly detects
“regularities” and “anomalies” in data that are plain random.

At the cost of appearing biased, I have to say that the literary mind
can be intentionally prone to the confusion between noise and meaning ,
that is, between a randomly constructed arrangement and a precisely
intended message. However, this causes little harm; few claim that art is
a tool of investigation of the Truth - rather than an attempt to escape it
or make it more palatable. Symbolism is the child of our inability and
unwillingness to accept randomness; we give meaning to all manner of
shapes; we detect human figures in inkblots. I saw mosques in the clouds
announced Arthur Rimbaud the 19th-century French symbolic poet.
This interpretation took him to “poetic” Abyssinia (in East Africa),
where he was brutalized by a Christian Lebanese slave dealer,
contracted syphilis, and lost a leg to gangrene. He gave up poetry in
disgust at the age of 19, and died anonymously in a Marseilles hospital
ward while still in his thirties. But it was too late. European intellectual
life developed what seems to be an irreversible taste for symbolism - we
are still paying its price, with psychoanalysis and other fads.

Regrettably, some people play the game too seriously; they are paid
to read too much into things. All my life I have suffered the conflict
between my love of literature and poetry and my profound allergy to
most teachers of literature and “critics”. The French poet Paul Valery
was surprised to listen to a commentary of his poems that found
meanings that had until then escaped him (of course, it was pointed out
to him that these were intended by his subconscious).

More generally, we underestimate the share of randomness in about
anything, a point that may not merit a book - except when it is the
specialist who is the fool of all fools. Disturbingly, science has only
recently been able to handle randomness (the growth in available
information has been exceeded by the expansion of noise). Probability
theory is a young arrival in mathematics; probability applied to practice
is almost nonexistent as a discipline.

Consider the left and the right columns of Table P.l. The best way to
summarize the major thesis of this book is that it addresses situations
(many of them tragicomical) where the left column is mistaken for the

PROLOGUE

3

Table P.l Table of Confusion

Presenting the central distinctions used in the book

GENERAL

Luck

Randomness
Probability
Belief, conjecture
Theory

Anecdote, coincidence
Forecast

Skills

Determinism

Certainty

Knowledge, certitude
Reality

Causality, law
Prophecy

MARKET PERFORMANCE

Lucky idiot Skilled investor

Survivorship bias Market outperformance

FINANCE

Volatility Return (or drift)

Stochastic variable Deterministic variable

PHYSICS AND ENGINEERING

Noise Signal

LITERARY CRITICISM

None (literary critics do Symbol

not seem to have a name
for things they do not
understand)

PHILOSOPHY OF SCIENCE

Epistemic probability Physical probability

Induction Deduction

Synthetic proposition Analytic proposition

right one. The sub-sections also illustrate the key areas of discussion on
which this book will be based.

The reader may wonder whether the opposite case might not deserve
some attention, that is, the situations where non-randomness is
mistaken for randomness. Shouldn’t we be concerned with situations
where patterns and messages may have been ignored? I have two
answers. First, I am not overly worried about the existence of

4

PROLOGUE

undetected patterns. We have been reading lengthy and complex
messages in just about any manifestation of nature that presents
jaggedness (such as the palm of a hand, the residues at the bottom of
Turkish coffee cups, etc.). Armed with home supercomputers and
chained processors, and helped by complexity and “chaos” theories, the
scientists, semi-scientists, and pseudoscientists will be able to find
portents. Second, we need to take into account the costs of mistakes; in
my opinion, mistaking the right column for the left one is not as costly
as an error in the opposite direction. Even popular opinion warns that
bad information is worse than no information at all.

However interesting these areas could be, their discussion would be a
tall order. In addition, they are not my current professional specialty.
There is one world in which I believe the habit of mistaking luck for skill
is most prevalent - and most conspicuous - and that is the world of
trading. By luck or misfortune, that is the world in which I operate. It is
my profession, and as such it will form the backbone of this book. It is
what I know best. In addition, business presents the best (and most
entertaining) laboratory for the understanding of these differences. For
it is the area of human undertaking where the confusion is greatest and
its effects the most pernicious. For instance, we often have the mistaken
impression that a strategy is an excellent strategy, or an entrepreneur a
person endowed with “vision”, or a trader an excellent trader, only to
realize that 9 9.9% of their past performance is attributable to chance,
and chance alone. Ask a profitable investor to explain the reasons for his
success; he will offer some deep and convincing interpretation of the
results. Frequently, these delusions are intentional and deserve to bear
the name “charlatanism”.

If there is one cause for this confusion between the left and the right
sides of our table, it is our inability to think critically - we may enjoy
presenting conjectures as truth. We are wired to be like that. We will see
that our mind is not equipped with the adequate hardware to handle
probabilities; such infirmity even strikes the expert, sometimes just the
expert. A critical mind, on the other hand, is someone who has the guts,
when confronting a given set of information, to attribute a large share of
its possible cause to the left column.

The 19th-century cartoon character, pot-bellied bourgeois Monsieur
Prudhomme, carried around a large sword with a double intent:

PROLOGUE

5

primarily to defend the Republic against its enemies, and secondarily to
attack it should it stray from its course. In the same manner, this book
has two purposes: to defend science (as a light beam across the noise of
randomness), and to attack the scientist when he strays from his course
(most disasters come from the fact that individual scientists do not have
an innate understanding of standard error or a clue about critical
thinking). As a practitioner of uncertainty I have seen more than my
share of snake-oil salesmen dressed in the garb of scientists. The greatest
fools of randomness will be found among these.

This author hates books that can be easily guessed from the table of
contents - but a hint of what comes next seems in order. The book is
composed of three parts. The first is an introspection into Solon’s
warning, as his outburst on rare events became my lifelong motto. In it
we meditate on visible and invisible histories. The second presents a
collection of probability biases I encountered (and suffered from) in my
career in randomness - ones that continue to fool me. The third
concludes the book with the revelation that perhaps ridding ourselves of
our humanity is not in the works; we need tricks, not some grandiose
moralizing help. Again the elders can help us with some of their ruses.

PART I

C roesus, King of Lydia, was considered the richest man of his time.

To this day Romance languages use the expression “rich as
Croesus” to describe a person of excessive wealth. He was said to be
visited by Solon, the Greek legislator known for his dignity, reserve,
upright morals, humility, frugality, wisdom, intelligence, and courage.
. Solon did not display the smallest surprise at the wealth and splendor
surrounding his host, nor the tiniest admiration for their owner. Croesus
was so irked by the manifest lack of impression on the part of this
illustrious visitor that he attempted to extract from him some
acknowledgment. He asked him if he had known a happier man than
him. Solon cited the life of a man who led a noble life and died while in
battle. Prodded for more, he gave similar examples of heroic but
terminated lives, until Croesus, irate, asked him point-blank if he was
not to be considered the happiest man of all. Solon answered: “The
observation of the numerous misfortunes that attend all conditions
forbids us to grow insolent upon our present enjoyments, or to admire a
man’s happiness that may yet, in course of time, suffer change. For the
uncertain future has yet to come, with all variety of future; and him only
to whom the divinity has [guaranteed] continued happiness until the end
we may call happy .” 1

The modern equivalent has been no less eloquently voiced by the
baseball coach Yogi Berra, who seems to have translated Solon’s

10

SOLON’S WARNING

outburst from the pure Attic Greek into no less pure Brooklyn English
with “it ain’t over until it’s over”, or, in a less dignified manner, with “it
ain’t over until the fat lady sings”. In addition, aside from his use of the
vernacular, the Yogi Berra quote presents an advantage of being true,
while the meeting between Croesus and Solon was one of these
historical facts that benefited from the imagination of the chroniclers, as
it was chronologically impossible for the two men to have been in the
same location.

Part I is concerned with the degree to which a situation may yet, in
the course of time, suffer change. For we can be tricked by situations
involving mostly the activities of the Goddess Fortuna - Jupiter’s
firstborn daughter. Solon was wise enough to get the following point;
that which came with the help of luck could be taken away by luck (and
often rapidly and unexpectedly at that). The flipside, which deserves to
be considered as well (in fact it is even more of our concern), is that
things that come with little help from luck are more resistant to
randomness. Solon also had the intuition of a problem that has obsessed
science for the past three centuries. It is called the problem of induction.
I call it in this book the black swan or the rare event. Solon even
understood another linked problem, which I call the skewness issue; it
does not matter how frequently something succeeds if failure is too
costly to bear.

Yet the story of Croesus has another twist. Having lost a battle to the
redoubtable Persian king Cyrus, he was about to be burned alive when
he called Solon’s name and shouted (something like) “Solon, you were
right” (again this is legend). Cyrus asked about the nature of such
unusual invocations, and he told him about Solon’s warning. This
impressed Cyrus so much that he decided to spare Croesus’ life, as he
reflected on the possibilities as far as his own fate was concerned. People
were thoughtful at that time.

An illustration of the effect of randomness on social pecking
order and jealousy, through two characters of opposite
attitudes. On the concealed rare event. How things in modern
life may change rather rapidly, except, perhaps, in dentistry.

Nero Tulip

HIT BY LIGHTNING

N ero Tulip became obsessed with trading after witnessing a strange
scene one spring day as he was visiting the Chicago Mercantile
Exchange. A red convertible Porsche, driven at several times the city
speed limit, abruptly stopped in front of the entrance, its tires emitting
the sound of pigs being slaughtered. A visibly demented athletic man in
his thirties, his face flushed red, emerged and ran up the steps as if he
were chased by a tiger. He left the car double-parked, its engine running,
provoking an angry fanfare of horns. After a long minute, a bored
young man clad in a yellow jacket (yellow was the color reserved for
clerks) came down the steps, visibly untroubled by the traffic

12

SOLON’S WARNING

commotion. He drove the car into the underground parking garage -
perfunctorily as if it were his daily chore.

That day Nero Tulip was hit with what the French call a coup de
foudre, a sudden intense (and obsessive) infatuation that strikes like
lightning. “This is for me!”, he screamed enthusiastically - he could not
help comparing the life of a trader to the alternative lives that could
present themselves to him. Academia conjured up the image of a silent
university office with rude secretaries; business, the image of a quiet
office staffed with slow thinkers and semi-slow thinkers who express
themselves in full sentences.

TEMPORARY SANITY

Unlike a coup de foudre, the infatuation triggered by the Chicago
scene has not left him close to a decade-and-a-half after the incident. For
Nero swears that no other lawful profession in our times could be as
devoid of boredom as that of the trader. Furthermore, although he has
not yet practiced the profession of high-sea piracy, he is now convinced
that even the occupation of pirate would present more dull moments
than that of the trader.

Nero could best be described as someone who randomly (and
abruptly) swings between the deportment and speech manners of a
church historian and the verbally abusive intensity of a Chicago pit
trader. He can commit hundreds of millions of dollars in a transaction
without a blink or a shadow of second thoughts, yet agonize between
two appetizers on the menu, changing his mind back and forth and
wearing out the most patient of waiters.

Nero holds an undergraduate degree in ancient literature and
mathematics from Cambridge University. He enrolled in a Ph.D.
program in statistics at the University of Chicago but, after completing
the prerequisite coursework, as well as the bulk of his doctoral research,
he switched to the philosophy department. He called the switch “a
moment of temporary sanity”, adding to the consternation of his thesis
director who warned him against philosophers and predicted his return
back to the fold. He finished writing his thesis in philosophy. But not the
Derrida continental style of incomprehensible philosophy (that is,

IF YOU’RE SO RICH WHY AREN’T YOU SO SMART?

13

incomprehensible to anyone outside of their ranks, like myself). It was
quite the opposite; his thesis was on the methodology of statistical
inference in its application to the social sciences. In fact, his thesis was
indistinguishable from a thesis in mathematical statistics - it was just a
bit more thoughtful (and twice as long).

It is often said that philosophy cannot feed its man - but that was not
the reason Nero left. He left because philosophy cannot entertain its
man. At first, it started looking futile; he recalled his statistics thesis
director’s warnings. Then, suddenly, it started to look like work. As he
became tired of writing papers on some arcane details of his earlier
papers, he gave up the academy. These academic debates bored him to
tears, particularly when very small minute points (invisible to the non-
initiated) were at stake. Action was what Nero required. The problem,
however, was that he selected the academy in the first place in order to
kill what he detected was the flatness and tempered submission of
employment life.

After witnessing the scene of the trader chased by a tiger, Nero found
a trainee spot on the Chicago Mercantile Exchange, the large exchange
where traders transact by shouting and gesticulating frenetically. There
he worked for a prestigious (but eccentric) local, who trained him in the
Chicago style, in return for Nero solving his mathematical equations.
The energy in the air proved motivating to Nero. He rapidly graduated
to the rank of self-employed trader. Then, when he got tired of standing
on his feet in the crowd, and straining his vocal cords, he decided to seek
employment “upstairs”, that is, trading from a desk. He moved to the
New York area and took a position with an investment house.

Nero specialized in quantitative financial products, in which he had an
early moment of glory, became famous and in demand. Many investment
houses in New York and London flashed huge guaranteed bonuses at
him. Nero spent a couple of years shuttling between New York and
London, attending important “meetings” and wearing expensive suits.
But soon Nero went into hiding; he rapidly pulled back to anonymity -
the Wall Street stardom track did not quite fit his temperament. To stay a
“hot trader” requires some organizational ambitions and a power hunger
that he feels lucky not to possess. He was only in it for the fun - and his
idea of fun does not include administrative and managerial work. He is
susceptible to conference room boredom and is incapable of talking to

14

SOLON’S WARNING

businessmen, particularly those run-of-the-mill variety. Nero is allergic
to the vocabulary of business talk, not just on plain aesthetic grounds.
Words like “game plan”, “bottom line”, “how to get there from here”,
“we provide our clients with solutions”, “our mission” and other
hackneyed expressions that dominate meetings lack both the precision
and the coloration that he prefers to hear. Whether people populate
silence with hollow sentences, or if such meetings present any true merit,
he does not know; at any rate he did not want to be part of it. Indeed
Nero’s extensive social life includes almost no business people. But
unlike me (I can be extremely humiliating when someone rubs me the
wrong way with inelegant pompousness), Nero handles himself with
gentle aloofness in these circumstances.

So, Nero switched career to what is called proprietary trading.
Traders are set up as independent entities, internal funds with their own
allocation of capital. They are left alone to do as they please, provided
of course that their results satisfy the executives. The name proprietary
comes from the fact that they trade the company’s own money. At the
end of the year they receive between 7% and 12% of the profits
generated. The proprietary trader has all the benefits of self
employment, and none of the burdens of running the mundane details
of his own business. He can work any hours he likes, can travel at a
whim and engage in all manner of personal pursuits. It is paradise for an
intellectual like Nero who dislikes manual work and values unscheduled
meditation. He has been doing that for the past ten years, in the
employment of two different trading firms.

MODUS OPERANDI

A word on Nero’s methods. He is as conservative a trader as one can be
in such a business. In the past he has had good years and less than good
years - but virtually no truly “bad” years. Over these years he has slowly
built for himself a stable nest egg, thanks to an income ranging between
$300,000 and (at the peak) $2,500,000. On average, he manages to
accumulate $500,000 a year in after-tax money (from an average income
of about $1,000,000); this goes straight into his savings account. In
1993, he had a flat year and was made to feel uncomfortable in his

IF YOU’RE SO RICH WHY AREN’T YOU SO SMART?

15

company. Other traders made out much better, so the capital at his
disposal was severely reduced, and he was made to feel undesirable at the
institution. He then went to get an identical job, down to an identically
designed workspace, but in a different firm that was friendlier. In the fall
of 1994 the traders who had been competing for the great performance
award blew up in unison during the worldwide bond market crash that
resulted from the random tightening by the Federal Reserve Bank of the
United States. They are all currently out of the market, performing a
variety of tasks. This business has a high mortality rate.

Why doesn’t Nero make more money? Because of his trading style -
or perhaps his personality. His risk aversion is extreme. Nero’s objective
is not to maximize his profits, so much as it is to avoid having this
entertaining money machine called trading taken away from him.
Blowing up would mean returning to the tedium of the university or the
non-trading life. Every time his risks increase, he conjures up the image
of the quiet hallway at the university, the long mornings at his desk
spent in revising a paper, kept awake by bad coffee. No, he does not
want to have to face the solemn university library where he was bored to
tears. “I am shooting for longevity”, he is wont to say.

Nero has seen many traders blow up, and does not want to get into
that situation. Blow up in the lingo has a precise meaning; it does not
just mean to lose money; it means to lose more money than one ever
expected, to the point of being thrown out of the business (the
equivalent of a doctor losing his license to practice or a lawyer being
disbarred). Nero rapidly exits trades after a predetermined loss. He
never sells “naked options” (a strategy that would leave him exposed to
large possible losses). He never puts himself in a situation where he can
lose more than, say, $1,000,000 - regardless of the probability of such
an event. That amount has always been variable; it depends on his
accumulated profits for the year. This risk aversion prevented him from
making as much money as the other traders on Wall Street who are
often called “Masters of the Universe”. The firms he has worked for
generally allocate more money to traders with a different style, like John
whom we will encounter soon.

Nero’s temperament is such that he does not mind losing small
money. “I love taking small losses”, he says. “I just need my winners to
be large”. In no circumstances does he want to be exposed to those rare

16

SOLON’S WARNING

events, like panics and sudden crashes that wipe a trader out in a flash.
To the contrary, he wants to benefit from them. When people ask him
why he does not hold on to losers, he invariably answers that he was
trained by “the most chicken of them all”, the Chicago trader Stevo who
taught him the business. This is not true; the real reason is his training in
probability and his innate skepticism.

There is another reason why Nero is not as rich as others in his
situation. His skepticism does not allow him to invest any of his own
money outside of treasury bonds. He therefore missed out on the great bull
market. The reason he offers is that it could have turned out to be a bear
market and a trap. Nero harbors a deep suspicion that the stock market is
some form of an investment scam and cannot bring himself to own a stock.
The difference with people around him who were enriched by the stock
market was that he was cash-flow rich, but his assets did not inflate at all
along with the rest of the world (his treasury bonds hardly changed in
value). He contrasts himself with one of those startup technology
companies that were massively cash-flow negative, but for which the
hordes developed some infatuation. This allowed the owners to become
rich from their stock valuation, and thus dependent on the randomness of
the market’s election of the winner. The difference with his friends of the
investing variety is that he did not depend on the bull market, and,
accordingly, does not have to worry about a bear market at all. His net
worth is not a function of the investment of his savings - he does not want
to depend on his investments, but on his cash earnings, for his enrichment.
He takes not an inch of risk with his savings, which he invests in the safest
possible vehicles. Treasury bonds are safe; they are issued by the United
States Government, and governments can hardly go bankrupt since they
can freely print their own currency to pay back their obligation.

NO WORK ETHICS

Today, at 39, after 14 years in the business, he can consider himself
comfortably settled. His personal portfolio contains several million
dollars in medium maturity Treasury Bonds, enough to eliminate any
worry about the future. What he likes most about proprietary trading is
that it requires considerably less time than other high-paying

IF YOU’RE SO RICH WHY AREN’T YOU SO SMART?

17

professions; in other words it is perfectly compatible with his non-
middle-class work ethics. Trading forces someone to think hard; those
who merely work hard generally lose their focus and intellectual energy.
In addition, they end up drowning in randomness; work ethics, Nero
believes, draw people to focus on noise rather than the signal (the
difference we established in Table P.l on page 3).

This free time has allowed him to carry on a variety of personal
interests. As Nero reads voraciously and spends considerable time in the
gym and museums, he cannot have a lawyer’s or a doctor’s schedule.
Nero found the time to go back to the statistics department where he
started his doctoral studies and finished the “harder science” doctorate
in statistics, by rewriting his thesis in more concise terms. Nero now
teaches, once a year, a half-semester seminar called History of
Probabilistic Thinking in the mathematics department of New York
University, a class of great originality that draws excellent graduate
students. He has saved enough money to be able to maintain his lifestyle
in the future and has contingency plans perhaps to retire into writing
popular essays of the scientific-literary variety, with themes revolving
around probability and indeterminism - but only if some event in the
future causes the markets to shut down.

THERE ARE ALWAYS SECRETS

Nero’s probabilistic introspection may have been helped out by some
dramatic event in his life - one that he kept to himself. A penetrating
observer might detect in Nero a measure of suspicious exuberance, an
unnatural drive. For his life is not as crystalline as it may seem. Nero
harbors a secret, one that will be discussed in time.

John the High-Yield Trader

Through most of the 1990s, across the street from Nero’s house stood
John’s - a much larger one. John was a high-yield trader, but he was not

18

SOLON’S WARNING

a trader in the style of Nero. A brief professional conversation with him
would have revealed that he presented the intellectual depth and
sharpness of mind of an aerobics instructor (though not the-physique). A
purblind man could have seen that John had been doing markedly better
than Nero (or, at least, felt compelled to show it). He parked two top-
of-the-line German cars in his driveway (his and hers), in addition to
two convertibles (one of which was a collectible Ferrari), while Nero
had been driving the same VW cabriolet for almost a decade - and still
does.

The wives of John and Nero were acquaintances, of the health-club
type of acquaintance, but Nero’s wife felt extremely uncomfortable in
the company of John’s. She felt that the lady was not merely trying to
impress her, but was treating her like someone inferior. While Nero had
become inured to the sight of traders getting rich (and trying too hard to
become sophisticated by turning into wine collectors and opera lovers),
his wife had rarely encountered repressed new wealth - the type of
people who have felt the sting of indigence at some point in their lives
and want to get even by exhibiting their wares. The only dark side of
being a trader, Nero often says, is the sight of money being showered on
unprepared people who are suddenly taught that Vivaldi’s Four Seasons
is “refined” music. But it was hard for his spouse to be exposed almost
daily to the neighbor who kept boasting of the new decorator they just
hired. John and his wife were not the least uncomfortable with the fact
that their “library” came with the leather-bound books (her readings at
the health club was limited to People Magazine but her shelves included
a selection of untouched books by dead American authors). She also
kept discussing unpronounceable exotic locations where they would
repair during their vacations without so much as knowing the smallest
thing about the place - she would have been hard put to explain in
which continent the Seychelles Islands were located. Nero’s wife is all
too human; although she kept telling herself that she did not want to be
in the shoes of John’s wife, she felt as if she had been somewhat
swamped in the competition of life. Somehow words and reason became
ineffectual in front of an oversized diamond, a monstrous house, and a
sports car collection.

IF YOU’RE SO RICH WHY AREN’T YOU SO SMART?

19

AN OVERPAID HICK

Nero also suffered the same ambiguous feeling towards his neighbors.
He was quite contemptuous of John, who represented about everything
he is not and does not want to be - but there was the social pressure that
was starting to weigh in on him. In addition, he too would like to have
sampled such excessive wealth. Intellectual contempt does not control
personal envy. That house across the street kept getting bigger, with
addition after addition - and Nero’s discomfort kept apace. While Nero
had succeeded beyond his wildest dreams, both personally and intellec-
tually, he was starting to consider himself as having missed a chance
somewhere. In the pecking order of Wall Street, the arrival of such types
as John had caused him no longer to be a significant trader - but while
he used to not care about this, John and his house and his cars had
started to gnaw away at him. All would have been well if Nero had not
had that stupid large house across the street judging him with a
superficial standard every morning. Was it the genetic pecking order at
play, with John’s house size making him a beta male? Worse even, John
was about five years his junior, and, despite a shorter career, was
making at least ten times his income.

When they used to run into each other Nero had a clear feeling that
John tried to put him down - with barely detectable but no less potent
signs of condescension. Some days John ignored him completely. Had
John been a remote character, one Nero could only read about in the
papers, the situation would have been different. But there John was in
flesh and bones and he was his neighbor. The mistake Nero made was to
start talking to him, as the rule of pecking order immediately emerged.
Nero tried to soothe his discomfort by recalling the behavior of Swann,
the character in Proust’s In Search of Time Lost, a refined art dealer and
man of leisure who was at ease with such men as his personal friend the
then Prince of Wales, but acted like he had to prove something in the
presence of the middle class. It was much easier for Swann to mix with
the aristocratic and well established set of Guermantes than it was with
the social-climbing one of the Verdurins, no doubt because he was far
more confident in their presence. Likewise Nero can exact some form of
respect from prestigious and prominent people. He regularly takes long
meditative walks in Paris and Venice with an erudite Nobel prize-caliber

20

SOLON'S WARNING

scientist (the kind of person who no longer has to prove anything) who
actively seeks his conversation. A very famous billionaire speculator calls
him regularly to ask him his opinion on the valuation of some derivative
securities. But there he was obsessively trying to gain the respect of some
overpaid hick with a cheap New Jersey “Noo-Joyzy” accent. (Had I been
in Nero’s shoes I would have paraded some of my scorn to John with the
use of body language, but again, Nero is a nice person.)

Clearly, John was not as well educated, well bred, physically fit, or
perceived as being as intelligent as Nero - but that was not all; he was
not even as street-smart as him! Nero has met true street-smart people in
the pits of Chicago who exhibit a rapidity of thinking that he could not
detect in John. Nero was convinced that the man was a confident
shallow-thinker who had done well because he never made an allowance
for his vulnerability. But Nero could not, at times, repress his envy - he
wondered whether it was an objective evaluation of John, or if it was his
feelings of being slighted that led him to such an assessment of John.
Perhaps it was Nero who was not quite the best trader. Maybe if he had
pushed himself harder or had sought the right opportunity - instead of
“thinking”, writing articles and reading complicated papers. Perhaps he
should have been involved in the high-yield business, where he would
have shined among those shallow-thinkers like John.

So Nero tried to soothe his jealousy by investigating the rules of
pecking order. Psychologists Kahneman and Tversky showed that most
people prefer to make $70,000 when others around them are making
$60,000 than to make $80,000 when others around them are making
$90,000. Economics, schmeconomics, it is all pecking order, he thought.
No such analysis could prevent him from assessing his condition in an
absolute rather than a relative way. With John, Nero felt that, for all his
intellectual training, he was just another one of those who would prefer
to make less money provided others made even less.

Nero thought that there was at least one piece of evidence to support
the idea of John being merely lucky - in other words Nero, after all,
might not need to move away from his neighbor’s starter palazzo. There
was hope that John would meet his undoing. For John seemed unaware
of one large hidden risk he was taking, the risk of blow up, a risk he
could not see because he had too short an experience of the market (but
also because he was not thoughtful enough to study history). How could

IF YOU'RE SO RICH WHY AREN’T YOU SO SMART?

21

John, with his coarse mind, otherwise be making so much money? This
business of junk bonds depends on some knowledge of the “odds”, a
calculation of the probability of the rare (or random) events. What do
such fools know about odds? These traders use “quantitative tools” that
give them the odds - and Nero disagrees with the methods used. This
high-yield market resembles a nap on a railway track. One afternoon,
the surprise train would run you over. You make money every month
for a long time, then lose a multiple of your cumulative performance in a
few hours. He has seen it with option sellers in 1987, 1989, 1992, and
1998. One day they are taken off the exchange floors, accompanied by
oversized security men, and nobody ever sees them again. The big house
is simply a loan; John might end up as a luxury car salesman somewhere
in New Jersey, selling to the new newly rich who no doubt would feel
comfortable in his presence. Nero cannot blow up. His less oversized
abode, with its 4,000 books, is his own. No market event can take it
away from him. Every one of his losses is limited. His trader’s dignity
will never, never, be threatened.

John, for his part, thought of Nero as a loser, and a snobbish over-
educated loser at that. Nero was involved in a mature business. He
believed that he was way over the hill. “These ‘prop’ traders are dying”,
he used to say. “They think they are smarter than everybody else, but
they are passe”.

The Red-Hot Summer

Finally, in September 1998, Nero was vindicated. One morning while
leaving to go to work he saw John in his front yard unusually smoking a
cigarette. He was not wearing a business suit. He looked humble; his
customary swagger was gone. Nero immediately knew that John had
been fired. What he did not suspect was that John also lost almost
everything he had. We will see more details of John’s losses in Chapter 5.

Nero felt ashamed of his feelings of schadenfreude , the joy humans
can experience upon their rivals’ misfortune. But he could not repress it.
Aside from it being unchivalrous, it was said to bring bad luck (Nero is

22

SOLON’S WARNING

weakly superstitious). But in this case, Nero’s merriment did not come
from the fact that John went back to his place in life, so much as it was
from the fact that Nero’s methods, beliefs, and track -record had
suddenly gained in credibility. Nero would be able to raise public money
on his track record precisely because such a thing could not possibly
happen to him. A repetition of such an event would pay off massively
for him. Part of Nero’s elation also came from the fact that he felt proud
of his sticking to his strategy for so long, in spite of the pressure to be the
alpha male. It was also because he would no longer question his trading
style when others were getting rich because they misunderstood the
structure of randomness and market cycles.

SEROTONIN AND RANDOMNESS

Can we judge the success of people by their raw performance and their
personal wealth? Sometimes - but not always. We will see how, at any
point in time, a large section of businessmen with outstanding track
records will be no better than randomly thrown darts. More curiously,
and owing to a peculiar bias, cases will abound of the least-skilled
businessmen being the richest. However, they will fail to make an
allowance for the role of luck in their performance.

Lucky fools do not bear the slightest suspicion that they may be
lucky fools - by definition, they do not know that they belong to such
category. They will act as if they deserved the money. Their strings of
successes will inject them with so much serotonin (or some similar
substance) that they will even fool themselves about their ability to
outperform markets (our hormonal system does not know whether our
successes depend on randomness). One can notice it in their posture; a
profitable trader will walk upright, dominant style - and will tend to
talk more than a losing trader. Scientists found out that serotonin, a
neurotransmitter, seems to command a large share of our human
behavior. It sets a positive feedback, the virtuous circle, but, owing to
an external kick from randomness, can start a reverse motion and cause
a vicious circle. It has been shown that monkeys injected with serotonin
will rise in the pecking order, which in turn causes an increase of the
serotonin level in their blood - until the virtuous cycle breaks and starts

IF YOU’RE SO RICH WHY AREN’T YOU SO SMART?

23

a vicious one (during the vicious cycle failure will cause one to slide in
the pecking order, causing a behavior that will bring about further
drops in the pecking order). Likewise, an increase in personal
performance (regardless of whether it is caused deterministically or
by the agency of lady Fortuna) induces a rise of serotonin in the subject,
itself causing an increase of what is commonly called leadership ability.
One is “on a roll”. Some imperceptible changes in deportment, like an
ability to express oneself with serenity and confidence, makes the
subject look credible - as if he truly deserved the shekels. Randomness
will be ruled out as a possible factor in the performance, until it rears
its head once again and delivers the kick that will induce the vicious
cycle.

People have often had the bad taste of asking me in a social setting if
my day in trading was profitable. If my father were there, he would
usually stop them by saying “never ask a man if he is from Sparta: if he
were, he would have let you know such an important fact - and if he
were not, you could hurt his feelings”. Likewise, never ask a trader if he
is profitable; you can easily see it in his gesture and gait. People in the
profession can easily tell if traders are making or losing money; head
traders are quick at identifying an employee who is faring poorly. Their
.face will seldom reveal much, as people consciously attempt to gain
control of their facial expressions. But the way they walk, the way they
hold the telephone, and the hesitation in their behavior, will not fail to
reveal their true disposition. On the morning after John had been fired,
he certainly lost much of his serotonin - unless it was another substance
that researchers will discover in another decade. One cab driver in
i; Chicago explained to me that he could tell if traders he picked up near
; the Chicago Board of Trade, a futures exchange, were doing well. “They
get all puffed up”, he said. I found it interesting (and mysterious) that he
could detect it so rapidly. I later got some plausible explanation from
evolutionary psychology, which claims that such physical manifesta-
tions of one’s performance in life, just like an animal’s dominant
condition, can be used for signaling: it makes the winners seem easily
visible, which is efficient in mate selection.

24

SOLON’S WARNING

Your Dentist Is Rich, Very Rich

We close this chapter with a hint on the next discussion of resistance to
randomness. Recall that Nero can considered prosperous but not “very
rich” by his day’s standards. However, according to some strange
accounting measure we will see in the next chapter, he is extremely rich
on the average of lives he could have led - he takes so little risk in his
trading career that there could have been very few disastrous outcomes.
The fact that he did not experience John’s success was the reason he did
not suffer his downfall. He would be therefore wealthy according to this
unusual (and probabilistic) method of accounting for wealth. Recall that
Nero protects himself from the rare event. Had Nero had to relive his
professional life a few million times, very few sample paths would be
marred by bad luck - but, owing to his conservatism, very few as well
would be affected by extreme good luck. That is, his life in stability
would be similar to that of an ecclesiastic clock repairman. Naturally,
we are discussing only his professional life, excluding his (sometimes
volatile) private one.

Arguably, in expectation, a dentist is considerably richer than the
rock musician who is driven in a pink Rolls Royce, the speculator who
bids up the price of impressionist paintings, or the entrepreneur who
collects private jets. For one cannot consider a profession without taking
into account the average of the people who enter it, not the sample of
those who have succeeded in it. We will examine the point later from the
vantage point of the survivorship bias, but here, in Part I, we will look at
it with respect to Resistance to randomness.

Consider two neighbors, John Doe A, a janitor who won the New
Jersey lottery and moved to a wealthy neighborhood, compared to John
Doe B, his next-door neighbor of more modest condition who has been
drilling teeth eight hours a day over the past 35 years. Clearly one can
say that, thanks to the dullness of his career, if John Doe B had to relive
his life a few thousand times since graduation from dental school, the
range of possible outcomes would be rather narrow (assuming he is
properly insured). At the best, he would end up drilling the rich teeth of
the New York Park Avenue residents, while the worst would show him
drilling those of some semi-deserted town full of trailers in the Catskills.

IF YOU’RE SO RICH WHY AREN’T YOU SO SMART?

25

Furthermore, assuming he graduated from a very prestigious teeth-
drilling school, the range of outcomes would be even more compressed.
As to John Doe A, if he had to relive his life a million times, almost all of
them would see him performing janitorial activities (and spending
endless dollars on fruitless lottery tickets), and one in a million would
see him winning the New Jersey lottery.

The idea of taking into account both the observed and unobserved
possible outcomes sounds like lunacy. For most people, probability is
about what may happen in the future, not events in the observed past;
an event that has already taken place has 100% probability, i.e.,
certainty. I have discussed the point with many people who platitudi-
nously accuse me of confusing myth and reality. Myths, particularly
well-aged ones, as we saw with Solon’s warning, can be far more potent
(and provide us with more experience) than plain reality.

On alternative histories, a probabilistic view of the world,
intellectual fraud, and the randomness wisdom of a Frenchman
with steady bathing habits. How journalists are bred to not
understand random series of events. Beware borrowed wisdom:
how almost all great ideas concerning random outcomes are
against conventional sapience. On the difference between
correctness and intelligibility.

Alternative History

I start with the platitude that one cannot judge a performance in any
given field (war, politics, medicine, investments). by the results, but by
the costs of the alternative (i.e. if history played out in a different way).
Such substitute courses of events are called alternative histories. Clearly,
the quality of a decision cannot be solely judged based on its outcome,
but such a point seems to be voiced only by people who fail (those who
succeed attribute their success to the quality of their decision). Such
opinion is what politicians on their way out of office keep telling those
members of the press who still listen to them that they followed the best

A BIZARRE ACCOUNTING METHOD

27

course - eliciting the customary commiserating “yes, we know” that
makes the sting even worse. And like many platitudes, this one, while
being too obvious, is not easy to carry out in practice.

RUSSIAN ROULETTE

One can illustrate the strange concept of alternative histories as follows.
Imagine an eccentric (and bored) tycoon offering you $10 million to
play Russian roulette, i.e. to put a revolver containing one bullet in the
six available chambers to your head and pull the trigger. Each
realization would count as one history, for a total of six possible
histories of equal probabilities. Five out of these six histories would lead
to enrichment; one would lead to a statistic, that is, an obituary with an
embarrassing (but certainly original) cause of death. The problem is that
only one of the histories is observed in reality; and the winner of $10
million would elicit the admiration and praise of some fatuous journalist
(the very same ones who unconditionally admire the Forbes 500
billionaires). Like almost every executive I have encountered during a
15-year career on Wall Street (the role of such executives in my view
being no more than a judge of results delivered in a random manner),
the public observes the external signs of wealth without even having a
glimpse at the source (we call such source the generator). Consider the
possibility that the Russian roulette winner would be used as a role
model by his family, friends, and neighbors.

|* While the remaining five histories are not observable, the wise and
thoughtful person could easily make a guess as to their attributes. It
requires some thoughtfulness and personal courage. In addition, in time,
: if the roulette-betting fool keeps playing the game, the bad histories will
tend to catch up with him. Thus, if a 25-year-old played Russian
roulette, say, once a year, there would be a very slim possibility of his
surviving his 50th birthday - but, if there are enough players, say
thousands of 25-year-old players, we can expect to see a handful of
(extremely rich) survivors (and a very large cemetery). Here I have to
admit that the example of Russian roulette is more than intellectual to
me. I lost a comrade to this “game” during the Lebanese war, when we
were in our teens. But there is more. I discovered that I had more than a

28

SOLON’S WARNING

shallow interest in literature thanks to the effect of Graham Greene’s
account of his flirt with such a game; it bore a stronger effect on me than
the actual events I had recently witnessed. Greene claimed that he once
tried to soothe the dullness of his childhood by pulling the trigger on a
revolver - making me shiver at the thought that I had at least a one in six
probability of having been without his novels.

The reader can see my unusual notion of alternative accounting: $10
million earned through Russian roulette does not have the same value as
$10 million earned through the diligent and artful practice of dentistry.
They are the same, can buy the same goods, except that one’s dependence
on randomness is greater than the other. To an accountant, though, they
would be identical. To your next-door neighbor too. Yet, deep down, I
cannot help but consider them as qualitatively different. The notion of
such alternative accounting has interesting intellectual extensions and
lends itself to mathematical formulation, as we will see in the next
chapter with our introduction of the Monte Carlo engine. Note that such
use of mathematics is only illustrative, aiming at getting the intuition of
the point, and should not be interpreted as an engineering issue. In other
words, one need not actually compute the alternative histories so much
as assess their attributes. Mathematics is not just a “numbers game”, it is
a way of thinking. We will see that probability is a qualitative subject.

AN EVEN MORE VICIOUS ROULETTE

Reality is far more vicious than Russian roulette. First, it delivers the
fatal bullet rather infrequently, like a revolver that would have
hundreds, even thousands of chambers instead of six. After a few
dozen tries, one forgets about the existence of a bullet, under a numbing
false sense of security. The point is dubbed in this, book the black swan
problem, which we cover in Chapter 7, as it is linked to the problem of
induction, a problem that has kept a few philosophers of science awake
at night. It is also related to a problem called denigration of history as
gamblers, investors, and decision makers feel that the sort of things that
happen to others would not necessarily happen to them.

Second, unlike a well-defined precise game like Russian roulette,
where the risks are visible to anyone capable of multiplying and dividing

A BIZARRE ACCOUNTING METHOD

29

by six, one does not observe the barrel of reality. Very rarely is the
generator visible to the naked eye. One is thus capable of unwittingly
playing Russian roulette - and calling it by some alternative “low risk”
name. We see the wealth being generated, never the processor, a matter
that makes people lose sight of their risks, and never the losers. The
game seems terribly easy and we play along blithely.

Smooth Peer Relations

The degree of resistance to randomness in one's life is an abstract idea,
part of its logic counterintuitive, and, to confuse matters, its realizations
non-observable. But I have been increasingly devoted to it - for a
collection of personal reasons I will leave for later. Clearly my way of
judging matters is probabilistic in nature; it relies on the notion of what
could have probably happened, and requires a certain mental attitude
with respect to one’s observations. I do not recommend engaging an
accountant in a discussion about such probabilistic considerations. For
an accountant a number is a number. If he were interested in probability
he would have gotten involved in more introspective professions - and
would be inclined to make a costly mistake on your tax return.

While we do not see the roulette barrel of reality, some people give it
a try; it takes a special mindset to do so. Having seen hundreds of people
enter and exit my profession (characterized by extreme dependence on
randomness), I have to say that those who have had a modicum of
scientific training tend to go the extra mile. For many, such thinking is
second nature. This might not necessarily come from their scientific
training per se (beware of causality), but possibly from the fact that
people who have decided at some point in their lives to devote
themselves to scientific research tend to have an ingrained intellectual
curiosity and a natural tendency for such introspection. Particularly
thoughtful are those who had to abandon scientific studies because of
their inability to keep focused on a narrowly defined problem. Without
excessive intellectual curiosity it is almost impossible to complete a
Ph.D. thesis these days, but without a desire to narrowly specialize it is

30

SOLON’S WARNING

impossible to make a scientific career. (There is a distinction, however,
between the mind of a pure mathematician thriving on abstraction and
that of a scientist consumed by curiosity. A mathematician is absorbed
in what goes into his head while a scientist searches into what is outside
of himself.) However, some people’s concern for randomness can be
excessive; I have even seen people trained in some fields, like say,
quantum mechanics, push the idea to the other extreme, only seeing
alternative histories and ignoring the one that actually took place.

Some traders can be unexpectedly introspective about randomness. I
recently had dinner at the bar of the Odeon with Lauren R., a trader
who was reading a draft of this book. We flipped a coin to see who was
going to pay for the meal. I lost and paid. He was about to thank me
when he abruptly stopped and said: “Reading your book you would say
that I paid for half of it probabilistically”.

I thus view people distributed across two polar categories: on one
extreme, those who never accept the notion of randomness; on the
other, those who are tortured by it. When I started on Wall Street in the
1980s, trading rooms were populated with people with a “business
orientation”, that is, generally devoid of any introspection, flat as a
pancake, and likely to be fooled by randomness. Their failure rate was
extremely high, particularly when financial instruments gained in
complexity. Somehow tricky products, like exotic options, were
introduced and carried counterintuitive payoffs that were too difficult
for someone of such culture to handle. They dropped like flies; I do not
think that many of the hundreds of MBAs of my generation 1 met on
Wall Street in the 1980s still engage in such forms of professional and
disciplined risk taking.

SALVATION VIA AEROFLOT

The 1990s witnessed the arrival of people- of richer and more interesting
backgrounds, which made the trading rooms far more entertaining. I
was saved from the conversation of MBAs. Many scientists, some of
them extremely successful in their field, arrived with a desire to make a
buck. They, in turn, hired people who resembled them. While most of
these people were not Ph.D.s (indeed, the Ph.D. is still a minority), the

A BIZARRE ACCOUNTING METHOD

31

culture and values suddenly changed, becoming more tolerant of
intellectual depth. It caused an increase in the already high demand for
scientists on Wall Street, owing to the rapid development of financial
instruments. The dominant specialty was physics, but one could find all
manner of quantitative backgrounds among them. Russian, French,
Chinese, and Indian accents (by order) began dominating in both New
York and London. It was said that every plane from Moscow had at
least its back row full of Russian mathematical physicists en route to
Wall Street (they lacked the street smarts to get good seats). One could
hire very cheap labor by going to JFK airport with a (mandatory)
translator, randomly interviewing those that fitted the stereotype.
Indeed, by the late 1990s one could get someone trained by a world-
class scientist for almost half the price of an MBA. As they say,
marketing is everything; these guys do not know how to sell themselves.

I had a strong bias in favor of Russian scientists; many can be put to
active use as chess coaches (I also got a piano teacher out of the process).
In addition, they are extremely helpful in the interview process. When
MBAs apply for trading positions, they frequently boast “advanced”
chess skills on their resumes. I recall the MBA career counselor at
Wharton recommending our advertising chess skills “because it sounds
intelligent and strategic”. MBAs, typically, can interpret their superficial
knowledge of the rules of the game into “expertise”. We used to verify
the accuracy of claims of chess expertise (and the character of the
applicant) by pulling a chess set out of a drawer and telling the student,
now turning pale: “Yuri will have a word with you”.

The failure rate of these scientists, though, was better, but only
slightly so than that of MBAs; but it came from another reason, linked
to their being on average (but only on average) devoid of the smallest bit
of practical intelligence. Some successful scientists had the judgment
(and social graces) of a door knob - but by no means all of them. Many
people were capable of the most complex calculations with utmost rigor
when it came to equations, but were totally incapable of solving a
problem with the smallest connection to reality; it was as if they
understood the letter but not the spirit of the math. I am convinced that
X, a likeable Russian man of my acquaintance, has two brains: one for
math and another, considerably inferior one, for everything else (which
included solving problems related to the mathematics of finance). But on

32

SOLON'S WARNING

occasion a fast-thinking scientific-minded person with street smarts
would emerge. Whatever the benefits of such population shift, it
improved our chess skills and provided us with quality conversation
during lunchtime - it extended the lunch hour considerably. Consider
that I had in the 1980s to chat with colleagues who had an MBA or tax
accounting background and were capable of the heroic feat of discussing
FASB standards. I have to say that their interests were not too
contagious. The interesting thing about these physicists does not lie in
their ability to discuss fluid dynamics; it is that they were naturally
interested in a variety of intellectual subjects and provide pleasant
conversation.

SOLON VISITS REGINE’S NIGHT CLUB

As the reader may already suspect, my opinions about randomness have
not earned me the smoothest of relations with some of my peers during
my Wall Street career (many of whom the reader can see indirectly - but
only indirectly - portrayed in these chapters). But where I had uneven
relations was with some of those who had the misfortune of being my
bosses. For I had two bosses in my life of contrasting characteristics in
about every trait.

The first, whom I will call Kenny, was the epitome of the suburban
family man. He would be of the type to coach soccer on Saturday
morning, and invite his brother-in-law for a Sunday afternoon barbecue.
He gave the appearance of someone I would trust with my savings -
indeed he rose quite rapidly in the institution in spite of his lack of
technical competence in financial derivatives (his firm’s claim to fame).
But he was too much a no-nonsense person to make out my logic. He
once blamed me for not being impressed with the successes of some of his
traders who did well during the bull market for European bonds of 1993,
whom I openly considered nothing better than random gunslingers. I
tried presenting him with the notion of survivorship bias (Part II of this
book) in vain. His traders have all exited the business since then “to
pursue other interests” (including him). But he gave the appearance of
being a calm, measured man, who spoke his mind and knew how to put
the other person at ease during a conversation. He was articulate,

A BIZARRE ACCOUNTING METHOD

33

extremely presentable thanks to his athletic looks, well measured in his
speech, and was endowed with the extremely rare quality of being an
excellent listener. His personal charm allowed him to win the confidence
of the chairman - but I could not conceal my disrespect, particularly as
he could not make out the nature of my conversation. In spite of his
conservative looks he was a perfect time bomb, ticking away.

The second, whom I will call Jean-Patrice, in contrast, was a moody
Frenchman with an explosive temper and a hyper-aggressive personality.
Except for those he truly liked (not that many), he was expert at making
his subordinates uncomfortable, putting them in a state of constant
anxiety. He greatly contributed to my formation as a risk-taker; he is one
of the very rare people who have the guts to care only about the
generator, entirely oblivious of the results. He presented the wisdom of
Solon, but, while one would expect someone with such personal wisdom
and such understanding of randomness to lead a dull life, he lived a
colorful one. In contrast with Kenny, who wore conservative dark suits
and white shirts (his only indulgence was flashy equestrian Hermes ties),
Jean-Patrice dressed like a peacock: blue shirts, plaid sports coats stuffed
with gaudy silk pocket squares. No family-minded man, he rarely came to
work before noon - though I can safely say that he carried his work with
him to the most unlikely places. He frequently called me from Regine’s,
an upscale night-club in New York, waking me up at three in the morning
to discuss some small (and irrelevant) details of my risk exposure. In spite
of his slight corpulence, women seemed to find him irresistible; he
frequently disappeared at midday and was unreachable for hours. His
advantage might have been in his being a New York Frenchman with
steady bathing habits. Once, recently, he invited me to discuss an urgent
business issue with him. Characteristically, I found him mid-afternoon in
a strange “club” in Paris that carried no nameplate and where he sat with
documents strewn across the table from him. Sipping champagne, he was
simultaneously caressed by two scantily dressed young ladies. Strangely,
he involved them in the conversation as if they were part of the meeting.
He even had one of the ladies pick up his constantly ringing mobile phone
as he did not want our conversation to be interrupted.

I am still amazed at this flamboyant man’s obsession with risks, which
he constantly played in his head - he literally thought of everything that
could possibly happen. He forced me to make an alternative plan should

34

SOLON’S WARNING

a plane crash into the office building - and fumed at my answer that the
financial condition of his department would be of small interest to me in
such circumstances. He had a horrible reputation as a philanderer, a
temperamental boss capable of firing someone at a whim, yet he listened
to me and understood every word I had to say, encouraging me to go the
extra mile in my study of randomness. He taught me to look for the
invisible risks of blowup in any portfolio. Not coincidentally, he has an
immense respect for science and an almost fawning deference for
scientists; a decade or so after we worked together he showed up
unexpectedly during the defense of my doctoral thesis, smiling from the
back of the room. While Kenny knew how to climb the ladder of an
institution, reaching a high level in the organization before being forced
out, Jean-Patrice did not have such a happy career, a matter that taught
me to beware of mature financial institutions.

It can be disturbing for many self-styled “bottom line” oriented
people to be questioned about the histories that did not take place rather
than the ones that actually happened. Clearly, to a no-nonsense person
of the “successful in business” variety, my language (and, I have to
reckon, some traits of my personality) appear strange and incompre-
hensible. To my amusement, the argument appears offensive to many.

The contrast between Kenny and Jean-Patrice is not a mere coin-
cidence in a protracted career. Beware the spendthrift “businesswise”
person; the cemetery of markets is disproportionately well stocked with
the self-styled “bottom line” people. In contrast with their customary
Masters of the Universe demeanor, they suddenly look pale, humble and
hormone-deprived on the way to the personnel office for the customary
discussion of the severance agreement.

George Will Is No Solon:
On Counterintuitive, Truths

Realism can be punishing. Probabilistic skepticism is worse. It is difficult
to go about life wearing probabilistic glasses, as one starts seeing fools
of randomness all around, in a variety of situations - obdurate in their

A BIZARRE ACCOUNTING METHOD

35

perceptional illusion. To start, it is impossible to read a historian’s
analysis without questioning the inferences: we know that Hannibal and
Hitler were mad in their pursuits, as Rome is not today Phoenician-
speaking and Times Square in New York currently exhibits no
swastikas. But what of all those generals who were equally foolish,
but ended up winning the war and consequently the esteem of the
historical chronicler? It is hard to think of Alexander the Great or Julius
Caesar as men who won only in the visible history, but who could have
suffered defeat in others. If we have heard of them, it is simply because
they took considerable risks, along with thousands of others and
happened to win. They were intelligent, courageous, noble (at times),
had the highest possible obtainable culture in their day - but so did
thousands of others who live in the musty footnotes of history. Again I
am not contesting that they won their wars - only the claims concerning
the quality of their strategies. (My very first impression upon a recent
rereading of the Iliad, the first in my adulthood, is that the epic poet did
not judge his heroes by the result: heroes won and lost battles in a
manner that was totally independent of their own valor; their fate
depended upon totally external forces, generally the explicit agency of
the scheming gods (not devoid of nepotism). Heroes are heroes because
they are heroic in behavior, not because they won or lost. Patrocles does
not strike us as a hero because of his accomplishments (he was rapidly
killed) but because he preferred to die than see Achilles sulking into
inaction. Clearly the epic poets understood invisible histories. Also later
thinkers and poets had more elaborate methods for dealing with
randomness, as we will see with stoicism.)

Listening to the media, mostly because I am not used to it, can cause
me on occasion to jump out of my seat and become emotional in front
of the moving image (I grew up with no television and was in my late
twenties when I learned to operate a TV set). One illustration of a
dangerous refusal to consider alternative histories is provided by the
interview that media person George Will, a “commentator” of the
extensively commenting variety, conducted with Professor Robert
Shiller, a man known to the public for his best-selling book Irrational
Exuberance, but known to the connoisseur for his remarkable insights
about the structure of market randomness and volatility (expressed in
the precision of mathematics).

36

SOLON’S WARNING

The interview is illustrative of the destructive aspect of the media, in
catering to our heavily warped common sense and biases. I was told that
George Will was very famous and extremely respected (that is, for a
journalist). He might even be someone of utmost intellectual integrity;
his profession, however, is merely to sound smart and intelligent to the
hordes. Shiller, on the other hand, understands the ins and outs of
randomness; he is trained to deal with rigorous argumentation, but does
sound less smart in public because his subject matter is highly
counterintuitive. Shiller had been pronouncing the stock market to be
overpriced for a long time. George Will indicated to Shiller that had
people listened to him in the past they would have lost money, as the
market has more than doubled since he started pronouncing it
overvalued. To such a journalistic and well sounding (but senseless)
argument, Shiller was unable to respond except to explain that the fact
that he was wrong in one single market call should not carry undue
significance. Shiller, as a scientist, did not claim being a prophet or one
of the entertainers who comment on the markets on the evening news.
Yogi Berra would have had a better time with his confident comment on
the fat lady not having sung yet.

I could not understand what Shiller, untrained to compress his ideas
into vapid sound-bites, was doing on such a TV show. Clearly, it is
foolish to think that an irrational market cannot become even more
irrational; Shiller’s views on the rationality of the market are not
invalidated by the argument that he was wrong in the past. Here I could
not help seeing in the person of George Will the representative of so
many nightmares in my career; my attempting to prevent someone from
playing Russian roulette for $10 million and seeing journalist George
Will humiliating me in public by saying that had the person listened to
me it would have cost him a considerable fortune. In addition, Will’s
comment was not an off-the-cuff remark; he wrote an article on the
matter discussing Shiller’s bad “prophecy”. Such tendency to make and
unmake prophets based on the fate of the roulette wheel is symptomatic
of our genetic inability to cope with the complex structure of
randomness prevailing in the modern world. Mixing forecast and
prophecy is symptomatic of randomness foolishness (prophecy belongs
to the right column, forecast is its mere left-column equivalent).

A BIZARRE ACCOUNTING METHOD

37

HUMILIATED IN DEBATES

Clearly, this idea of alternative history does not make intuitive sense,
which is where the fun begins. For starters, we are not wired in a way to
understand probability, a point that we will examine backward and
forward in this book. I will just say at this point that researchers of the
brain believe that mathematical truths make little sense to our mind,
particularly when it comes to the examination of random outcomes.
Most results in probability are entirely counterintuitive; we will see
plenty of them. Then why argue with a mere journalist whose paycheck
comes from playing on the conventional wisdom of the hordes? I recall
that every time I have been humiliated in a public discussion on markets
by someone (of the George Will variety) who seemed to present more
palatable and easier to understand arguments, I turned out (much later)
to be right. I do not dispute that arguments should be simplified to their
maximum potential; but people often confuse complex ideas that cannot
be simplified into a media-friendly statement as symptomatic of a
confused mind. MBAs learn the concept of clarity and simplicity, the
five-minute-manager take on things. The concept may apply to the
business plan for a fertilizer plant, but not to highly probabilistic
arguments - which is the reason 1 have anecdotal evidence in my
business that MBAs tend to blow up in financial markets, as they are
trained to simplify matters a couple of steps beyond their requirement (I
beg the MBA reader not to take offense; I am myself the unhappy holder
of the degree).

Beware the confusion between correctness and intelligibility. Part of
conventional wisdom favors things that can be explained rather
instantly and “in a nutshell” - in many circles it is considered law.
Having attended a French elementary school, a lycee primaire, I was
trained to rehash the popular adage:

Ce qui se congoit bien s’enonce clairement

Et les mots pour le dire viennent aisement

What is easy to conceive is clear to express/Words to say it would come
effortlessly.

The reader can imagine my disappointment at realizing, while

38

SOLON’S WARNING

growing up as a practitioner of randomness, that most poetic sounding
adages are plain wrong. Borrowed wisdom can be vicious. I need to
make a huge effort not to be swayed by well-sounding remarks. I remind
myself of Einstein’s remark that common sense is nothing but a
collection of misconceptions acquired by age 18. Furthermore: what
sounds intelligent in a conversation or a meeting, or, particularly in the
media, is suspicious.

Any reading of the history of science would show that almost all the
smart things that have been proven by science appeared like lunacies at
the time they were first discovered. Try to explain to a London Times
journalist in 1905 that time slows down when one travels (even the Nobel
committee never granted Einstein the prize on account of his insight on
special relativity). Or to someone with no exposure to physics that there
are places in our universe where time does not exist. Try to explain to
Kenny that, although his star trader had made him a lot of money, I have
enough arguments to convince him that he is a dangerous idiot.

RISK MANAGERS

Corporations and financial institutions have recently created the strange
position of risk manager, someone who is supposed to monitor the
institution and verify that it is not too deeply involved in the business of
playing Russian roulette. Clearly, having been burned a few times, the
incentive is there to have someone take a look at the generator, the
roulette that produces the profits and losses. Although it is more fun to
trade, many Extremely smart people among my friends (including Jean-
Patrice) felt attracted by such positions. It is an important and attractive
fact that the average risk manager earns more than the average trader
(particularly when we take into account the number of traders thrown
out of the business). But their job feels strange, for the following reason:
as we said, the generator of reality is not observable. They are limited in
their power to stop profitable traders from taking risks, given that they
would, ex post be accused by the George Wills around of costing the
shareholder some precious opportunity shekels. On the other hand, the
occurrence of a blowup would cause them to be responsible for it. What
to do in such circumstances?

A BIZARRE ACCOUNTING METHOD

39

Their focus becomes to play politics, cover themselves by issuing
vaguely phrased internal memoranda that warn against risk-taking
activities yet stop short of completely condemning it, lest they lose their
job. Like a doctor torn between the two types of errors, the false positive
(telling the patient he has cancer when in fact he does not) and the false
negative (telling the patient he is healthy when in fact he has cancer),
they need to balance their existence with the fact that they inherently
need some margin of error in their business. For my part, I resolved the
problem long ago by being both the risk manager and the boss at my
current operation.

I conclude the chapter with a presentation of the central paradox of
my career in financial randomness. By definition, I go against the grain,
so it should come as no surprise that my style and methods are neither
popular nor easy to understand. But I manage money for others, and the
world is not just populated with babbling but ultimately inconsequential
journalists with no money to invest. So my wish is for investors in
general to remain fools of randomness (so I can trade against them), yet
that there remain a minority intelligent enough to value my methods and
supply me with capital. I was fortunate to meet Donald Sussman who
corresponds to such ideal investor; he helped me in the second stage of
my career by backing the startup of Empirica, my trading firm, thus
freeing me from the ills of Wall Street employment. My greatest risk is
to become successful, as it would mean that my business is about to
disappear; strange business, ours.

THREE

On Monte Carlo simulation as a metaphor to understanding a
sequence of random historical events. On randomness and
artificial history. Age is beauty, almost always, and the new and
the young are generally toxic. Send your history professor to an
introductory class on sampling theory.

EUROPLAYBOY MATHEMATICS

T he stereotype of a pure mathematician presents an anemic man
with a shaggy beard and grimy and uncut fingernails silently
laboring on a Spartan but disorganized desk. With thin shoulders and a
pot belly, he sits in a grubby office, totally absorbed in his work,
oblivious to the grunginess of his surroundings. He grew up in a
communist regime and speaks English with an astringent and throaty
Eastern European accent. When he eats, crumbs of food accumulate in
his beard. With time he becomes more and more absorbed in his subject
matter of pure theorems, reaching levels of ever increasing abstraction.
The American public was recently exposed to one of these characters
with the unabomber, the bearded and recluse mathematician who lived
in a hut and took to murdering people who promoted modern

A MATHEMATICAL MEDITATION ON HISTORY

41

technology. No journalist was capable of even coming close to
describing the subject matter of his thesis, Complex Boundaries, as it
has no intelligible equivalent - a complex number being an entirely
abstract and imaginary number, the square root of minus one, an object
that has no analog outside of the world of mathematics.

The name Monte Carlo conjures up the image of a suntanned urbane
man of the Europlayboy variety entering a casino under a whiff of the
Mediterranean breeze. He is an apt skier and tennis player, but also can
hold his own in chess and bridge. He drives a gray sports car, dresses in
a well ironed Italian handmade suit, and speaks carefully and smoothly
about mundane, but real, matters, those a journalist can easily describe
to the public in compact sentences. Inside the casino he astutely counts
the cards, mastering the odds, and bets in a studied manner, his mind
producing precise calculations of his optimal betting size. He could be
James Bond’s smarter lost brother.

Now when I think of Monte Carlo mathematics, I think of a happy
combination of the two: the Monte Carlo man’s realism without the
shallowness combined with the mathematician’s intuitions without the
excessive abstraction. For indeed this branch of mathematics is of
immense practical use - it does not present the same dryness commonly
associated with mathematics. I became addicted to it the minute I
became a trader. It shaped my thinking in most matters related to
randomness. Most of the examples used in the book were created with
my Monte Carlo generator, which I introduce in this chapter. Yet, it is
far more a way of thinking than a computational method. Mathematics
is principally a tool to meditate, rather than to compute.

THE TOOLS

The notion of alternative histories discussed in the last chapter can be
extended considerably and subjected to all manner of technical refine-
ment. This brings us to the tools used in my profession to toy with
uncertainty. I will outline them next. Monte Carlo methods, in brief,
consist in creating artificial history using the following concepts.

First, consider the sample path. The invisible histories have a scien-
tific name, alternative sample paths, a name borrowed from the field of

42

SOLON’S WARNING

mathematics of probability called stochastic processes. The notion of
path, as opposed to outcome, indicates that it is not a mere MBA-style
scenario analysis, but the examination of a sequence of scenarios along
the course of time. We are not just concerned at where a bird can end up
tomorrow night, but rather at all the various places it can possibly visit
during the time interval. We are not concerned with what the investor’s
worth would be in, say, a year, but rather of the heart-wrenching rides
he may experience during that period. The word sample stresses that
one sees only one realization among a collection of possible ones. Now a
sample path can be both deterministic or random, which brings the next
distinction.

A random sample path , also called a random run, is the mathematical
name for such succession of virtual historical events, starting at a given
date and ending at another, except that they are subjected to some
varying level of uncertainty. However, the word random should not be
mistaken for equiprobable (i.e. having the same probability). Some
outcomes will give a higher probability than others. An example of a
random sample path can be the body temperature of your explorer
cousin during his latest bout with typhoid fever, measured hourly from
the beginning to the end of his episode. It can also be a simulation of the
price of your favorite technology stock, measured daily at the close of
the market, over, say, one year. Starting at $100, in one scenario it can
end up at $20 having seen a high of $220, in another it can end up at
$145 having seen a low of $10. Another example is the evolution of
your wealth during an evening at a casino. You start with $1000 in your
pocket, and measure it every 15 minutes. In one sample path you have
$2200 at midnight; in another you barely have $20 left for a cab fare.

Stochastic processes refer to the dynamics of events unfolding with
the course of time. Stochastic is a fancy Greek name for random. This
branch of probability concerns itself with the study of the evolution of
successive random events - one could call it the mathematics of history.
The key about a process is that it has time in it.

What is a Monte Carlo generator? Imagine that you can replicate a
perfect roulette wheel in your attic without having recourse to a
carpenter. Computer programs can be written to simulate just about
anything. They are even better (and cheaper) than the roulette wheel
built by your carpenter, as this may be inclined to favor one number

A MATHEMATICAL MEDITATION ON HISTORY

43

more than others owing to a possible slant in its build or the floor of
your attic. These are called the biases.

Monte Carlo simulations are closer to a toy than anything I have seen
in my adult life. One can generate thousands, perhaps millions of
random sample paths, and look at the prevalent characteristics of some
of their features. The assistance of the computer is instrumental in such
studies. The glamorous reference to Monte Carlo indicates the
metaphor of simulating the random events in the manner of a virtual
casino. One sets conditions believed to resemble the ones that prevail in
reality, and launches a collection of simulations around possible events.
With no mathematical literacy we can launch a Monte Carlo simulation
of an 18-year-old Christian Lebanese playing successively Russian
roulette for a given sum, and see how many of these attempts result in
enrichment, or how long it takes on average before he hits the obituary.
We can change the barrel to contain 500 holes, a matter that would
decrease the probability of death, and see the results.

Monte Carlo simulation methods were pioneered in martial physics
in the Los Alamos laboratory during the A bomb preparation. They
became popular in financial mathematics in the 1980s, particularly in
the theories of the random walk of asset prices. Clearly, we have to say
that the example of Russian roulette does not need such apparatus, but
many problems, particularly those resembling real-life situations,
require the potency of a Monte Carlo simulator.

MONTE CARLO MATHEMATICS

It is a fact that “true” mathematicians do not like Monte Carlo methods.
They believe that they rob us of the finesse and elegance of mathematics.
They call it “brute force”. For we can replace a large portion of
mathematical knowledge with a Monte Carlo simulator (and other
computational tricks). For instance, someone with no formal knowledge
of geometry can compute the mysterious, almost mystical Pi. How? By
drawing a circle inside of a square, and “shooting” random bullets into
the picture (as in an arcade), specifying equal probabilities of hitting any
point on the map (something called a uniform distribution). The ratio of
bullets inside the circle divided by those inside and outside the circle will

44

SOLON’S WARNING

deliver a multiple of the mystical Pi, with possibly infinite precision.
Clearly, this is not an efficient use of a computer as Pi can be computed
analytically, that is, in a mathematical form, but the method can give
some users more intuition about the subject matter than lines of
equations. Some people’s brains and intuitions are oriented in such a
way that they are more capable of getting a point in such a manner (I
count myself one of those). The computer might not be natural to our
human brain; neither is mathematics.

I am not a “native” mathematician, that is, I am someone who does
not speak mathematics as a native language, but someone who speaks it
with a trace of a foreign accent. For I am not interested in mathematical
properties per se, only in the application, while a mathematician would
be interested in improving mathematics (via theorems and proofs). I
proved incapable of concentrating on deciphering a single equation
unless I was motivated by a real problem (with a modicum of greed);
thus most of what I know comes from derivatives trading - options
pushed me to study the math of probability. Many compulsive
gamblers, who otherwise would be of middling intelligence, acquire
remarkable card-counting skills thanks to their passionate greed.

Another analogy would be with grammar; mathematics is often
tedious and insightless grammar. There are those who are interested in
grammar for grammar’s sake, and those interested in avoiding solecisms
while writing documents. We are called “quants” - like physicists, we
have more interest in the employment of the mathematical tool than in
the tool itself. Mathematicians are born, never made. Physicists and
quants too. I do not care about the “elegance” and “quality” of the
mathematics I use so long as I can get the point right. I have recourse to
Monte Carlo machines whenever I can. They can get the work done.
They are also far more pedagogical, and I will use them in this book for
the examples.

Indeed, probability is an introspective field of inquiry, as it affects
more than one science, particularly the mother of all sciences; that of
knowledge. It is impossible to assess the quality of the knowledge we
are gathering without allowing a share of randomness in the manner it
is obtained and cleaning the argument from the chance coincidence that
could have seeped into its construction. In science, probability and
information are treated in exactly the same manner. Literally every

A MATHEMATICAL MEDITATION ON HISTORY

45

great thinker has dabbled with it, most of them obsessively. The two
greatest minds to me, Einstein and Keynes, both started their
intellectual journeys with it. Einstein wrote a major paper in 1905, in
which he was almost the first to examine in probabilistic terms the
succession of random events, namely the evolution of suspended
particles in a stationary liquid. His theory on the theory of the
Brownian movement can be used as the backbone of the random walk
theories used in financial modeling. As for Keynes, to the literate person
he is not the political economist that tweed-clad leftists love to quote,
but the author of the magisterial, introspective, and potent Treatise on
Probability. For before his venturing into the murky field of political
economy, Keynes was a probabilist. He also had other interesting
attributes (he blew up trading his account after experiencing excessive
opulence - people’s understanding of probability does not translate into
their behavior).

The reader can guess that the next step from such probabilistic
introspection is to get drawn into philosophy, particularly the branch of
philosophy that concerns itself with knowledge, called epistemology or
methodology, or philosophy of science, popularized by such persons as
Karl Popper and George Soros. We will not get into the topic until later
in the book.

Fun In My Attic

MAKING HISTORY

In the early 1990s, like many of my friends in quantitative finance, I
became addicted to the various Monte Carlo engines, which I taught
myself to build, thrilled to feel that I was generating history, a
Demiurgus. It can be electrifying to generate virtual histories and watch
the dispersion between the various results. Such dispersion is indicative
of the degree of resistance to randomness. This is where I am convinced
that I have been extremely lucky in my choice of career: one of the
attractive aspects of my profession as a quantitative option trader is that

46

SOLON’S WARNING

I have close to 95 % of my day free to think, read, and research (or
“reflect” in the gym, on ski slopes, or, more effectively, on a park
bench). I also had the privilege of frequently “working” from my well-
equipped attic.

The dividend of the computer revolution to us did not come in the
flooding of self-perpetuating e-mail messages and access to chat rooms;
it was in the sudden availability of fast processors capable of generating
a million sample paths per minute. Recall that I never considered myself
better than an unenthusiastic equation solver and was rarely capable of
prowess in the matter - being better at setting up equations than solving
them. Suddenly, my engine allowed me to solve with minimal effort the
most intractable of equations. Few solutions became out of reach.

ZORGLUBS CROWDING THE ATTIC

My Monte Carlo engine took me on a few interesting adventures. While
my colleagues were immersed in news stories, central bank
announcements, earnings reports, economic forecasts, sports results
and, not least, office politics, I started toying with it in fields bordering
my home base of financial probability. A natural field of expansion for
the amateur is evolutionary biology - the universality of its message and
its application to markets are appealing. I started simulating
populations of fast mutating animals called Zorglubs under climatic
changes and witnessing the most unexpected of conclusions - some of
the results are recycled in Chapter 5. My aim, as a pure amateur fleeing
the boredom of business life, was merely to develop intuitions for these
events - the sort of intuitions that amateurs build away from the overly
detailed sophistication of the professional researcher. 1 also toyed with
molecular biology, generating randomly occurring cancer cells and
witnessing some surprising aspects to their evolution. Naturally the
analogue to fabricating populations of Zorglubs was to simulate a
population of “idiotic bull”, “impetuous bear” and “cautious” traders
under different market regimes, say booms and busts, and to examine
their short-term and long-term survival. Under such a structure, “idiotic
bull” traders who get rich from the rally would use the proceeds to buy
more assets, driving prices higher, until their ultimate shellacking.

A MATHEMATICAL MEDITATION ON HISTORY

47

Bearish traders, though, rarely made it in the boom to get to the bust.
My models showed almost nobody to really ultimately make money;
bears dropped out like flies in the rally and bulls got ultimately
slaughtered, as paper profits vanished when the music stopped. But
there was one exception; some of those who traded options (I called
them option buyers) had remarkable staying power and I wanted to be
one of those. How? Because they could buy the insurance against
blowup; they could get anxiety-free sleep at night, thanks to the
knowledge that if their careers were threatened, it would not be owing
to the outcome of a single day.

If the tone of this book seems steeped in the culture of Darwinism and
evolutionary thinking, it does not come from any remotely formal
training in the natural sciences, but from the evolutionary way of
thinking taught by my Monte Carlo simulators.

I have to reckon that I outgrew the desire to generate random runs
every time I want to explore an idea - but by dint of playing with a
Monte Carlo engine for years I can no longer visualize a realized
outcome without reference to the non-realized ones. I call that
“summing under histories”, borrowing the expression from the colorful
physicist Richard Feynman who applied such methods to examine the
dynamics of particles.

Using my Monte Carlo to do and redo history reminded me of the
experimental novels (the so-called new novels) by such writers as Alain
Robbe-Grillet, popular in the 1960s and 1970s. There the same chapter
would be written and revised, the writer each time changing the plot like
a new sample path. Somehow the author was freed from the past
situation he helped create and allowed himself the indulgence to change
the plot retroactively.

DENIGRATION OF HISTORY

One more word on history seen from a Monte Carlo perspective. The
wisdom of such classical stories as Solon prods me to spend even more
time in the company of the classical historians, even if the stories, like
Solon’s warning, have benefited from the patina of time. However, this
goes against the grain: learning from history does not come naturally to

48

SOLON’S WARNING

us humans, a fact that is so visible in the endless repetitions of iden-
tically configured booms and busts in modern markets. By history I refer
to the anecdotes, not the historical theorizing, the .grand-scale
historicism that aims to interpret events with theories based on
uncovering some laws in the evolution of history - the sort of
Hegelianism and pseudoscientific historicism leading to such calls as
the end of history (it is pseudoscientific because it draws theories from
past events without allowing for the fact that such combinations of
events might have arisen from randomness; it is mostly pseudoscientific
because there is no way to verify the claims in a controlled experiment 2 ).
It is merely at the level of my desired sensibility, affecting the way I
would wish to think by reference to past events, by being able to better
steal the ideas of others and leverage them, correct the mental defect
that seems to block my ability to learn from others. It is the respect of
the elders that I would like to develop, reinforcing the awe I instinctively
feel for people with gray hair, but that has eroded in my life as a trader
where age and success are somewhat divorced. Indeed, I have two ways
of learning from history: from the past by reading the elders, and from
the future thanks to my Monte Carlo toy.

THE STOVE IS HOT

As I mentioned above, it is not natural for us to learn from history. We
have enough clues to believe that our genetic endowment as homo
erectus does not favor transfers of experience. It is a platitude that
children learn only from their own mistakes; they will cease to touch a
burning stove only when they are themselves burned; no possible
warning by others can lead to developing the smallest form of cautious-
ness. Adults, too, suffer from such a condition. This point has been
examined by behavioral economics pioneers Daniel Kahneman and
Amos Tversky with regards to the choices people make in selecting
risky medical treatments - I myself have seen it in my being extremely
lax in the area of detection and prevention (i.e., I refuse to derive my
risks from the probabilities computed on others, feeling that I am
somewhat special) yet extremely aggressive in the treatment of medical
conditions (I overreact when I am burned), which is not coherent with

A MATHEMATICAL MEDITATION ON HISTORY

49

rational behavior under uncertainty. This congenital denigration of the
experience of others is not limited to children or to people like myself; it
affects business decision makers and investors on a grand scale.

All of my colleagues whom I have known to denigrate history blew
up spectacularly - and I have yet to encounter some such person who
has not blown up. But the truly interesting point lies in the remarkable
similarities in their approaches. I have noticed plenty of analogies
between those who blew up in the stock market crash of 1987, those
who blew up in the Japan meltdown of 1990, those who blew up in the
bond market debacle of 1994, those who blew up in Russia in 1998, and
those who blew up buying Nasdaq stocks in 2000. They all made claims
to the effect that “these times are different” or that “their market was
different”, and offered seemingly well constructed intellectual
arguments (of an economic nature) to justify their claims; they were
unable to accept that the experience of others was out there, in the open,
freely available to all, with books detailing crashes in every bookstore.
Aside from these generalized systemic blow ups, I have seen hundreds of
option traders forced to leave the business after blowing up in a stupid
manner, in spite of warnings by the veterans, similar to a child’s
touching the stove. This I find to resemble my own personal attitude
with respect to the detection and prevention of the variety of ailments I
may be subjected to. Every man believes himself to be quite different, a
matter that amplifies the “why me?” shock upon a diagnosis.

We can discuss this point from different angles. Experts call one
manifestation of such denigration of history historical determinism. In a
nutshell we think that we would know when history is made; we believe
that people who, say, witnessed the stock market crash of 1929 knew
then that they lived an acute historical event, and that, should these
events repeat themselves, they would know about such facts. Life for us
is made to resemble an adventure movie, as we know ahead of time that
something big is about to happen. It is hard to imagine that people who
witnessed history did not know at the time how important the moment
was. Somehow all respect we may have for history does not translate
well into our treatment of the present.

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SOLON’S WARNING

MY SOLON

I have another reason to be obsessed with Solon’s warning. I hark back
to the very same strip of land in the Eastern Mediterranean where the
story took place. My ancestors experienced bouts of extreme opulence
and embarrassing penury over the course of a single generation, with
abrupt regressions that people around me who have the memory of
steady and linear betterment, do not think feasible (at least not at the
time of writing). Those around me either have (so far) had few family
setbacks (except for the great depression) or, more generally, are not
suffused with enough sense of history to reflect backward. For people of
my background, Eastern Mediterranean Greek-Orthodox and invaded
Eastern Roman citizens, it was as if our soul had been wired with the
remembrance of that sad April day circa 500 years ago when
Constantinople, under the invading Turks, fell out of history, leaving
us the lost subjects of a dead empire, very prosperous minorities in an
Islamic world - but with an extremely fragile wealth. Moreover, I
vividly remember the image of my own dignified grandfather, a former
deputy prime minister and son of a deputy prime minister (whom I never
saw without a suit), residing in a nondescript apartment in Athens, his
estate having been blown up during the Lebanese civil war. Incidentally,
having experienced the ravages of war, I find undignified
impoverishment far harsher than physical danger (somehow dying in
full dignity appears to me far preferable to living a janitorial life, which
is one of the reasons I dislike financial risks far more than physical
ones). I am certain that Croesus worried more about the loss of his
Kingdom than the perils to his life.

There is an important and non-trivial aspect of historical thinking,
perhaps more applicable to the markets than anything else: unlike many
“hard” sciences, history cannot lend itself to experimentation. But
somehow, overall, history is potent enough to deliver, on time, in the
medium to long run, most of the possible scenarios, burying the bad
guy. Bad trades catch up with you, it is frequently said in the markets.
Mathematicians of probability give that a fancy name: ergodicity. It
means, roughly, that (under certain conditions), very long sample paths
would end up resembling each other. The properties of a very, very long
sample path would be similar to the Monte Carlo properties of an

A MATHEMATICAL MEDITATION ON HISTORY

51

average of shorter ones. The janitor in Chapter 1 who won the lottery, if
he lived 1000 years, cannot be expected to win more lotteries. Those
who were unlucky in life in spite of their skills would eventually rise.
The lucky fool might have benefited from some luck in life; over the
longer run he would slowly converge to the state of a less-lucky idiot.
Each one would revert to his long-term properties.

Distilled Thinking on Your PalmPilot

BREAKING NEWS

The journalist, my bete noire , entered this book with George Will
dealing with random outcomes. In the next step I will show how my
Monte Carlo toy taught me to favor distilled thinking, by which I mean
the thinking based on information around us that is stripped of
meaningless but diverting clutter. For the difference between noise and
information, the topic of this book (noise has more randomness) has an
analog: that between journalism and history. To be competent, a
journalist should view matters like a historian, and play down the value
of the information he is providing, such as by saying: “today the market
went up, but this information is not too relevant as it emanates mostly
from noise”. He would certainly lose his job by trivializing the value of
the information in his hands. Not only is it difficult for the journalist to
think more like a historian, but it is alas the historian who is becoming
more like the journalist.

For an idea, age is beauty (it is premature to discuss the mathematics
of the point). The applicability of Solon’s warning to a life in random-
ness, in contrast with the exact opposite message delivered by the
prevailing media-soaked culture, reinforces my instinct to value distilled
thought over newer thinking, regardless of its apparent sophistication -
another reason to accumulate the hoary volumes by my bedside (I confess
that the only news items I currently read are the far more interesting
upscale social gossip stories found in Tatler, Paris Match and Vanity Fair
- in addition to The Economist). Aside from the decorum of ancient

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SOLON’S WARNING

thought as opposed to the coarseness of fresh ink, I spent some time
phrasing the idea in the mathematics of evolutionary arguments and
conditional probability. For an idea to have survived so long across so
many cycles is indicative of its relative fitness. Noise, at least some noise,
was filtered out. Mathematically, progress means that some new
information is better than past information, not that the average of
new information will supplant past information, which means that it is
optimal for someone, when in doubt, to systematically reject the new
idea, information, or method. Clearly and shockingly, always. Why?

The argument in favor of “new things” and even more “new new
things” goes as follows: look at the dramatic changes that have been
brought about by the arrival of new technologies, such as the
automobile, the airplane, the telephone, and the personal computer.
Middlebrow inference (inference stripped of probabilistic thinking)
would lead one to believe that all new technologies and inventions
would likewise revolutionize our lives. But the answer is not so obvious:
here we only see and count the winners, to the exclusion of the losers (it
is like saying that actors and writers are rich, ignoring the fact that
actors are largely waiters - and lucky to be ones for the less comely
writers usually serve French fries at McDonald’s). Losers? The Saturday
newspaper lists dozens of new patents of such items that can
revolutionize our lives. People tend to infer that because some inven-
tions have revolutionized our lives that inventions are good to endorse
and we should favor the new over the old. I hold the opposite view. The
opportunity cost of missing a “new new thing” like the airplane and the
automobile is minuscule compared to the toxicity of all the garbage one
has to go through to get to these jewels (assuming these have brought
some improvement to our lives, which I frequently doubt).

Now the exact same argument applies to information. The problem
with information is not that it is diverting and generally useless, but that
it is toxic. We will examine the dubious value of the highly frequent
news with a more technical discussion of signal filtering and observation
frequency further down. I will say here that such respect for the time
honored provides arguments to rule out any commerce with the
babbling modern journalist and implies a minimal exposure to the
media as a guiding principle for someone involved in decision-making
under uncertainty. If there is anything better than noise in the mass of

A MATHEMATICAL MEDITATION ON HISTORY

53

“urgent” news pounding us, it would be like a needle in a haystack.
People do not realize that the media is paid to get your attention. For a
journalist, silence rarely surpasses any word.

On the rare occasions when I boarded the 6:42 train to New York I
observed with amazement the hordes of depressed business commuters
(who seemed to have preferred to be elsewhere) studiously buried in the
Wall Street Journal , apprised of the minutiae of companies that, at the
time of writing, are probably out of business. Indeed it is difficult to
ascertain whether they seem depressed because they are reading the
newspaper, or if depressive people tend to read the newspaper, or if
people who are living outside their genetic habitat both read the
newspaper and look sleepy and depressed. But while early on in my
career such focus on noise would have offended me intellectually, as I
would have deemed such information as too statistically insignificant
for the derivation of any meaningful conclusion, I currently look at it
with delight. I am happy to see such mass-scale idiotic decision-making,
prone to overreaction in their post-perusal investment orders - in other
words I currently see in the fact that people read such material an
insurance for my continuing in the entertaining business of option
trading against the fools of randomness.

SHILLER REDUX

Much of the thinking about the negative value of information on society
in general was sparked by Robert Shiller. Not just in financial markets;
but overall his 1981 paper may be the first mathematically formulated
introspection on the manner society in general handles information.
Shiller made his mark with his 1981 paper on the volatility of markets,
where he determined that, if a stock price is the estimated value of
“something” (say the discounted cash flows from a corporation), then
market prices are way too volatile in relation to tangible manifestations
of that “something” (he used dividends as proxy). Prices swing more
than the fundamentals they are supposed to reflect, they visibly
overreact by being too high at times (when their price overshoots the
good news or when they go up without any marked reason) or too low
at others. The volatility differential between prices and information

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SOLON’S WARNING

meant that something about “rational expectation” did not work.
(Prices did not rationally reflect the long-term value of securities by
overshooting in either direction.) Markets had to be wrong. Shiller then
pronounced markets to be not as efficient as established by financial
theory (efficient markets meant, in a nutshell, that prices should adapt
to all available information in such a way as to be totally unpredictable
to us humans and prevent people from deriving profits). This conclusion
set off calls by the religious orders of high finance for the destruction of
the infidel who committed such apostasy. Interestingly, and by some
strange coincidence, it is that very same Shiller that was trounced by
George Will only one chapter ago.

The principal criticism against Shiller came from Robert C. Merton.
The attacks were purely on methodological grounds (Shiller’s analysis
was extremely rough; for instance, his using dividends in place of
earnings was rather weak). Merton was also defending the official
financial theory position that markets needed to be efficient and could
not possibly deliver opportunities on a silver plate. Yet the same Robert
C. Merton later introduced himself as the “founding partner” of a hedge
fund that aimed at taking advantage of market inefficiencies. Setting
aside the fact that Merton’s hedge fund blew up rather spectacularly
from the black swan problem (with characteristic denial), his “founding”
such a hedge fund requires, by implication, that he agrees with Shiller
about the inefficiency of the market. The defender of the dogmas of
modern finance and efficient markets started a fund that took advantage
of market inefficiencies! It is as if the Pope converted to Islam.

Things are not getting any better these days. At the time of writing,
news providers are 'offering all manner of updates, “breaking news” that
can be delivered electronically in a wireless manner. The ratio of
undistilled information to distilled is rising, saturating markets. The
elder’s messages need not be delivered to you as imminent news.

This does not mean that all journalists are fooled by randomness
noise providers: there are hordes of thoughtful ] ournalists in the business
(I would suggest London’s Anatole Kaletsky and New York’s Jim Grant
and Alan Abelson as the underrated representatives of such a class
among financial journalists; Gary Stix among scientific journalists); it is
just that prominent media journalism is a thoughtless process of
providing the noise that can capture people’s attention and there exists

A MATHEMATICAL MEDITATION ON HISTORY

55

no mechanism for separating the two. As a matter of fact smart
journalists are often penalized. Like the lawyer in Chapter 1 1 who does
not care about the truth, but about arguments that can sway a jury
whose intellectual defects he knows intimately, journalism goes to what
can capture our attention, with adequate sound-bites. Again my
scholarly friends would wonder why I am getting emotional stating
the obvious things about the journalists; the problem with my profession
is that we depend on them for what information we need to obtain.

GERONTOCRACY

A preference for distilled thinking implies favoring old investors and
traders, that is investors who have been exposed to markets the longest,
a matter that is counter to the common Wall Street practice of preferring
those that have been the most profitable, and preferring the younger
whenever possible. I toyed with Monte Carlo simulations of
heterogeneous populations of traders under a variety of regimes (closely
resembling historical ones), and found a significant advantage in
selecting aged traders, using, as a selection criterion their cumulative
years of experience rather than their absolute success (conditional on
their having survived without blowing up). “Survival of the fittest”, a
term so hackneyed in the investment media, does not seem to be
properly understood: under regime switching, as we will see in Chapter
5, it will be unclear who is actually the fittest, and those who will
survive are not necessarily those who appear to be the fittest. Curiously,
it will be the oldest, simply because older people have been exposed
longer to the rare event and can be, convincingly, more resistant to it. I
was amused to discover a similar evolutionary argument in mate
selection that considers that women prefer (on balance) to mate with
healthy older men over healthy younger ones, everything else being
equal, as the former provide some evidence of better genes. Gray hair
signals an enhanced ability to survive - conditional on having reached
the gray hair stage, he is likely to be more resistant to the vagaries of life.
Curiously, life insurers in renaissance Italy reached the same conclusion,
by charging the same insurance for a man in his 20s as they did for a
man in his 50s, a sign that they had the same life expectation; once a

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SOLON’S WARNING

man crossed the 40-year mark, he had shown that very few ailments
could harm him. We now proceed to a mathematical rephrasing of these
arguments.

Philostratus in Monte Carlo: On the Difference
Between Noise and Information

The wise man listens to meaning, the fool only gets the noise. The
modern Greek poet C. P. Cavafy wrote a piece in 1915 after
Philostratus’ adage: For the gods perceive things in the future, ordinary
people things in the present, but the wise perceive things about to
happen. Cavafy wrote:

in their intense meditation the hidden sound of things approaching

reaches them and they listen reverently while in the street outside the

people hear nothing at all.

I thought hard and long on how to explain with as little mathematics as
possible the difference between noise and meaning, and how to show
why the time scale is important in judging an historical event. The
Monte Carlo simulator can provide us with such an intuition. We will
start with an example borrowed from the investment world (that is my
profession), as it can be explained rather easily, but the concept can be
used in any application.

Let us manufacture a happily retired dentist, living in a pleasant
sunny town. We know a priori that he is an excellent investor, and that
he will be expected to earn a return of 15% in excess of Treasury bills,
with a 10% error rate per annum (what we call volatility). It means that
out of 100 sample paths, we expect close to 6 8 of them to fall within a
band of plus and minus 10% around the 15% excess return, i.e.
between 5% and 25% (to be technical; the bell-shaped normal distribu-
tion has 68% of all observations falling between —1 and 1 standard
deviations). It also means that 95 sample paths would fall between —5%
and 35%.

A MATHEMATICAL MEDITATION ON HISTORY

57

Clearly, we are dealing with a very optimistic situation. The dentist
builds for himself a nice trading desk in his attic, aiming to spend every
business day there watching the market, while sipping decaffeinated
cappuccino. He has an adventurous temperament, so he finds this
activity more attractive than drilling the teeth of reluctant old little Park
Avenue ladies.

He subscribes to a web-based service that supplies him with
continuous prices, now to be obtained for a fraction of what he pays
for his coffee. He puts his inventory of securities in his spreadsheet and
can thus instantaneously monitor the value of his speculative portfolio.
We are living in the era called that of connectivity.

A 15% return with a 10% volatility (or uncertainty) per annum
translates into a 93% probability of making money in any given year.
But seen at a narrow time scale, this translates into a mere 50.02%
probability of making money over any given second as shown in Table
3.1. Over the very narrow time increment, the observation will reveal
close to nothing. Yet the dentist’s heart will not tell him that. Being
emotional, he feels a pang with every loss, as it shows in red on his
screen. He feels some pleasure when the performance is positive, but not
in equivalent amount as the pain experienced when the performance is
negative.

At the end of every day the dentist will be emotionally drained. A
minute-by-minute examination of his performance means that each day
(assuming eight hours per day) he will have 241 pleasurable minutes
against 239 unpleasurable ones. These amount to 60,688 and 60,271,
respectively, per year. Now realize that if the unpleasurable minute is

Table 3.1 Probability of making money at different scales.

Scale

Probability

1 year

93%

1 quarter

77%

1 month

67%

1 day

54%

1 hour

51.3%

1 minute

50.17%

1 second

50.02%

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SOLON’S WARNING

worse in reverse pleasure than the pleasurable minute is in pleasure
terms, then the dentist incurs a large deficit when examining his
performance at a high frequency.

Consider the situation where the dentist examines his portfolio only
upon receiving the monthly account from the brokerage house. A s 67%
of his months will be positive, he incurs only four pangs of pain per
annum and eight uplifting experiences. This is the same dentist
following the same strategy. Now consider the dentist looking at his
performance only every year. Over the next 20 years that he is expected
to live, he will experience 19 pleasant surprises for every unpleasant
one!

This scaling property of randomness is generally misunderstood, even
by professionals. I have seen Ph.D.s argue over a performance observed
in a narrow time scale (meaningless by any standard). Before additional
dumping on the journalist, more observations seem in order.

Viewing it from another angle, if we take the ratio of noise to what
we call nonnoise (i.e., left column/right column), which we have the
privilege here of examining quantitatively, then we have the following.
Over one year we observe roughly 0.7 parts noise for every one part
performance. Over one month, we observe roughly 2.32 parts noise for
every one part performance. Over one hour, 30 parts noise for every one
part performance, and over one second, 1796 parts noise for every one
part performance.

A few conclusions:

1. Over a short time increment, one observes the variability of the
portfolio, not the returns. In other words, one sees the variance, little
else. I always remind myself that what one observes is at best a
combination of variance and returns, not just returns.

2. Our emotions are not designed to understand the point. The dentist
did better when he dealt with monthly statements rather than
infrequent ones. Perhaps it would be even better for him if he limited
himself to yearly statements.

3. When I see an investor monitoring his portfolio with live prices on
his cellular telephone or his PalmPilot, I smile and smile.

Finally I reckon that I am not immune to such an emotional defect. But I
deal with it by having no access to information, except in rare

A MATHEMATICAL MEDITATION ON HISTORY

59

circumstances. Again, I prefer to read poetry. If an event is important
enough, it will find its way to my ears. I will return to this point in time.

The same methodology can explain why the news (the high scale) is
full of noise and why history (the low scale) is largely stripped of it
(though fraught with interpretation problems). This explains why I
prefer not to read the newspaper (outside of the obituary), why I never
chitchat about markets, and, when in a trading room, I frequent the
mathematicians and the secretaries, not the traders. It explains why it is
better to read The Economist on Saturdays than the Wall Street Journal
every morning (from the standpoint of frequency, aside from the
massive gap in intellectual class between the two publications).

Finally, this explains why people who look too closely at randomness
burn out, their emotions drained by the series of pangs they experience.
Regardless of what people claim, a negative pang is not offset by a
positive one (some behavioral economists estimate the negative effect to
be up to 2.5 the magnitude of a positive one); it will lead to an
emotional deficit.

Some so-called wise and rational persons often blame me for
“ignoring” possible valuable information in the daily newspaper and
refusing to discount the details of the noise as “short-term events”. Some
of my employers have blamed me for living on a different planet.

My problem is that I am not rational and I am extremely prone to
drown in randomness and to incur emotional torture. I am aware of my
need to ruminate on park benches and in cafes away from information,
but I can only do so if I am somewhat deprived of it. My sole advantage
in life is that I know some of my weaknesses, mostly that I am incapable
of taming my emotions facing news and incapable of seeing a
performance with a clear head. Silence is far better. More on that in
Part III.

On extending the Monte Carlo generator to produce artificial
thinking and compare it with rigorous non-random constructs.
The science wars enter the business world. Why the aesthete in
me loves to be fooled by randomness.

Randomness and the Verb

O ur Monte > Carlo engine can take us into more literary territory.

Increasingly, a distinction is being made between the scientific
intellectual and the literary intellectual - culminating with what is called
the “science wars”, plotting factions of literate non-scientists against no
less literate scientists. The distinction between the two approaches
originated in Vienna in the 1930s, with a collection of physicists who
decided that the large gains in science were becoming significant enough
to make claims on the field known to belong to the humanities. In their
view, literary thinking could conceal plenty of well-sounding nonsense.
They wanted to strip thinking from rhetoric (except in literature and
poetry where it properly belonged).

RANDOMNESS, NONSENSE, AND THE SCIENTIFIC INTELLECTUAL 61

The way they introduced rigor into intellectual life is by declaring
that a statement could fall only into two categories: deductive , like “2 +
2 = 4”, i.e., incontrovertibly flowing from a precisely defined axiomatic
framework (here the rules of arithmetic), or inductive , i.e., verifiable in
some manner (experience, statistics, etc.), like “it rains in Spain” or
“New Yorkers are generally rude”. Anything else was plain
unadulterated hogwash (music could be a far better replacement to
metaphysics). Needless to say that inductive statements may turn out to
be difficult, even impossible, to verify, as we will see with the black
swan problem - and empiricism can be worse than any other form of
hogwash when it gives someone confidence (it will take me a few
chapters to drill the point). However, it was a good start to make
intellectuals responsible for providing some form of evidence for their
statements. This Vienna Circle was at the origin of the development of
the ideas of Wittgenstein, Popper, Carnap, and flocks of others.
Whatever merit their original ideas may have, the impact on both
philosophy and the practice of science has been significant. Some of
their impact on non-philosophical intellectual life is starting to develop,
albeit considerably more slowly.

One conceivable way to discriminate between a scientific intellectual
and a literary intellectual is by considering that a scientific intellectual can
usually recognize the writing of another but that the literary intellectual
would not be able to tell the difference between lines jotted down by a
scientist and those by a glib non-scientist. This is even more apparent
when the literary intellectual starts using scientific buzzwords, like
“uncertainty principle”, “Godel’s theorem”, “parallel universe”, or
“relativity” either out of context or, as often, in exact opposition to the
scientific meaning. I suggest reading the hilarious Fashionable Nonsense
by Alan Sokal for an illustration of such practice (I was laughing so loudly
and so frequently while reading it on a plane that other passengers kept
whispering things about me). By dumping the kitchen sink of scientific
references in a paper, one can make another literary intellectual believe
that one’s material has the stamp of science. Clearly, to a scientist, science
lies in the rigor of the inference, not in random references to such
grandiose concepts as general relativity or quantum indeterminacy. Such
rigor can be spelled out in plain English. Science is method and rigor; it
can be identified in the simplest of prose writing. For instance, what

62

SOLON’S WARNING

struck me while reading Richard Dawkins’ Selfish Gene 3 is that, although
the text does not exhibit a single equation, it seems as if it were translated
from the language of mathematics. Yet it is artistic prose.

REVERSE TURING TEST

Randomness can be of considerable help with the matter. For there is
another, far more entertaining way to make the distinction between the
babbler and the thinker. You can sometimes replicate something that can
be mistaken for a literary discourse with a Monte Carlo generator but it
is not possible randomly to construct a scientific one. Rhetoric can be
constructed randomly, but not genuine scientific knowledge. This is the
application of Turing’s test of artificial intelligence, except in reverse.
What is the Turing test? The brilliant British mathematician, eccentric,
and computer pioneer Alan Turing came up with the following test: a
computer can be said to be intelligent if it can (on average) fool a human
into mistaking it for another human. The converse should be true. A
human can be said to be unintelligent if we can replicate his speech by a
computer, which we know is unintelligent, and fool a human into
believing that it was written by a human. Can one produce a piece of
work that can be largely mistaken for Derrida entirely randomly?

The answer seems to be yes. Aside from the hoax by Alan Sokal (the
same of the hilarious book a few lines ago) who managed to produce
nonsense and get it published by some prominent journal , 4 there are
Monte Carlo generators designed to structure such texts and write entire
papers. Fed with “postmodernist” texts, they can randomize phrases
under a method called recursive grammar, and produce grammatically
sound but entirely meaningless sentences that sound like Jacques
Derrida, Camille Paglia, and such a crowd. Owing to the fuzziness of his
thought, the literary intellectual can be fooled by randomness.

At the Monash University program in Australia featuring the Dada
Engine built by Andrew C. Bulha , 5 I toyed with the engine and
generated a few papers containing the following sentences:

However, the main theme of the works of Rushdie is not theory, as
the dialectic paradigm of reality suggests, but pretheory. The premise

RANDOMNESS, NONSENSE, AND THE SCIENTIFIC INTELLECTUAL 63

of the neosemanticist paradigm of discourse implies that sexual
identity, ironically, has significance.

Many narratives concerning the role of the writer as observer may be
revealed. It could be said that if cultural narrative holds, we have to
choose between the dialectic paradigm of narrative and neo-
conceptual Marxism. Sartre’s analysis of cultural narrative holds
that society, paradoxically, has objective value.

Thus, the premise of the neodialectic paradigm of expression implies
that consciousness may be used to reinforce hierarchy, but only if
reality is distinct from consciousness ; if that is not the case, we can
assume that language has intrinsic meaning.

Some business speeches belong to this category in their own right,
except that they are less elegant and draw on a different type of
vocabulary than the literary ones. We can randomly construct a speech
imitating that of your chief executive officer to insure whether what he
is saying has value, or if it is merely dressed-up nonsense from someone
who was lucky to be put there. How? You select randomly five phrases
below, then connect them by adding the minimum required to construct
a grammatically sound speech.

We look after our customer’s interests/the road ahead/our assets are
our people/creation of shareholder value! our vision/our expertise lies
in/we provide interactive solutions/we position ourselves in this
market/how to serve our customers better/short term pain for long
term gain/we will be rewarded in the long run/we play from our
strength and improve our weaknesses! courage and determination will
prevail/we are committed to innovation and technology/a happy
employee is a productive employee! commitment to excellence!
strategic plan/our work ethics.

If this bears too close a resemblance to the speech you just heard from
the boss of your company, then I suggest looking for a new job.

64

SOLON’S WARNING

THE FATHER OF ALL PSEUDOTHINKERS

It is hard to resist discussion of artificial history without a comment on
the father of all pseudothinkers, Hegel. Hegel writes a jargon that is
meaningless outside of a chic Left-Bank Parisian cafe or the humanities
department of some university extremely well insulated from the real
world. I suggest this passage from the German “philosopher” (this
passage was detected, translated and reviled by Karl Popper):

Sound is the change in the specific condition of segregation of the
material parts, and in the negation of this condition ; merely an
abstract or an ideal ideality, as it were, of that specification. But this
change, accordingly, is itself immediately the negation of the material
specific subsistence; which is, therefore, real ideality of specific
gravity and cohesion, i.e. - heat. The heating up of sounding bodies,
just as of beaten and or rubbed ones, is the appearance of heat,
originating conceptually together with sound.

Even a Monte Carlo engine could not sound as random as the great
philosophical master thinker (it would take plenty of sample runs to get
the mixture of heat and sound). People call that philosophy and
frequently finance it with taxpayer subsidies! Now consider that
Hegelian thinking is generally linked to a “scientific” approach to
history; it has produced such results as Marxist regimes and even a
branch called “neo-Hegelian” thinking. These “thinkers” should be
given an undergraduate-level class on statistical sampling theory prior to
their release in the open world.

Monte Carlo Poetry

There are instances where I like to be fooled by randomness. My allergy
to nonsense and verbiage dissipates when it comes to art and poetry. On
the one hand, I try to define myself and behave officially as a no-
nonsense hyper-realist ferreting out the role of chance; on the other, I

RANDOMNESS, NONSENSE, AND THE SCIENTIFIC INTELLECTUAL 65

have no qualms indulging in all manner of personal superstitions. Where
do I draw the line? The answer is aesthetics. Some aesthetic forms
appeal to something genetic in us, whether or not they originate in
random associations or plain hallucination. Something in our human
genes is deeply moved by the fuzziness and ambiguity of language; then
why fight it?

The poetry and language-lover in me was initially depressed by the
account of the Exquisite Cadavers poetic exercise where interesting and
poetic sentences are randomly constructed. By throwing enough words
together, some unusual and magical-sounding metaphor is bound to
emerge according to the laws of combinatorics. Yet one cannot deny
that some of these poems are of ravishing beauty. Who cares about their
origin if they manage to please our aesthetic senses?

The story of the Exquisite Cadavers is as follows. In the aftermath of
the First World War, a collection of surrealist poets, which included
Andre Breton, their pope, Paul Eluard, and others got together in cafes
and tried the following exercise (modern literary critics attribute the
exercise to the depressed mood after the war and the need to escape
reality). On a folded piece of paper, in turn, each one of them would
write a predetermined part of a sentence, not knowing the other’s
choice. The first would pick an adjective, the second a noun, the third a
verb, the fourth an adjective, and the fifth a noun. The first publicized
exercise of such random (and collective) arrangement produced the
following poetic sentence:

The exquisite cadavers shall drink the new wine

(Les cadavres exquis boiront le vin nouveau). Impressive? It sounds even
more poetic in the native French. Quite impressive poetry was produced
in such a manner, sometimes with the aid of a computer. But poetry has
never been truly taken seriously outside of the beauty of its associations,
whether they have been produced by the random ranting of one or more
disorganized brains, or the more elaborate constructions of one
conscious creator.

Now regardless of whether the poetry was obtained by a Monte
Carlo engine or sung by a blind man in Asia Minor, language is potent
in bringing pleasure and solace. Testing its intellectual validity by

66

SOLON’S WARNING

translating it into simple logical arguments would rob it of a varying
degree of its potency, sometimes excessively; nothing can be more bland
than translated poetry. A convincing argument of the role of language is
the existence of surviving holy languages, uncorrupted by the no-
nonsense tests of daily use. Semitic religions, that is Judaism, Islam, and
original Christianity understood the point; keep a language away from
the rationalization of daily use and avoid the corruption of the
vernacular. Four decades ago, the Catholic church translated the
services and liturgies from Latin to the local vernaculars; it can be
argued that this caused a drop in religious beliefs. Suddenly religion
subjected itself to being judged by intellectual and scientific, without the
aesthetic, standards. The Greek Orthodox church made the lucky
mistake, upon translating some of its prayers from Church-Greek into
the Semitic-based vernacular spoken by the Grecosyrians of the Antioch
region (Southern Turkey and Northern Syria), of choosing classical
Arabic, an entirely dead language. My folks are thus lucky to pray in a
mixture of dead Koine (Church Greek) and no less dead Koranic
Arabic.

What does this point have to do with a book on randomness? Our
genes dictate a need for peche mignon. Even the economists, who
usually find abstruse ways completely to escape reality, are starting to
understand that what makes us tick is not necessarily the calculating
accountant in us. We do not need to be rational and scientific when it
comes to the details of our daily life - only in those that can harm us and
threaten our survival. Modern life seems to invite us to do the exact
opposite; become extremely realistic and intellectual when it comes to
such matters as religion and personal behavior, yet as irrational as
possible when it comes to markets and matters ruled by randomness. I
have encountered colleagues, “rational” no-nonsense people, who do
not understand why I cherish the poetry of Baudelaire or obscure (and
often impenetrable) writers like Elias Canetti, Borges, or Saint-John
Perse. Yet they get sucked into listening to the “analyses” of a television
“guru”, or into buying the stock of a company they know absolutely
nothing about, based on tips by neighbors who drive expensive cars.
The Vienna Circle, in their dumping on Hegel-style verbiage-based
philosophy, explained that, from a scientific standpoint, it was plain
garbage, and, from an artistic point of view, it was inferior to music. I

RANDOMNESS, NONSENSE, AND THE SCIENTIFIC INTELLECTUAL 67

have to say that I find Baudelaire far more pleasant to frequent than
CNN newscasters or listening to George Will.

There is a Yiddish saying: If 1 am going to be forced to eat pork, it
better be of the best kind. If I am going to be fooled by randomness, it
better be of the beautiful (and harmless) kind. This point will be made
again in Part III.

FIVE

SURVIVAL OF THE LEAST FIT -
CAN EVOLUTION BE FOOLED
BY RANDOMNESS?

A case study on two rare events. On rare events and evolution.

How “Darwinism” and evolution are concepts that are mis-
understood in the non-hiological world. Life is not continuous.
How evolution will be fooled by randomness. A preparation to
the problem of induction.

Carlos the Emerging Markets Wizard

I used to meet Carlos at a variety of New York parties, where he would
show up impeccably dressed, though a bit shy with the ladies. I used
to regularly pounce on him and try to pick his brains about what he did
for a living, namely buying or selling emerging market bonds. A nice
gentleman, he complied with my requests, but tensed up; for him
speaking English, in spite of his fluency, seemed to require some
expenditure of physical effort that made him contract his head and neck
muscles (some people are not made to speak foreign languages). What

SURVIVAL OF THE LEAST FIT

69

are emerging market bonds? “Emerging market” is the politically
correct euphemism to define a country that is not very developed (as a
skeptic, I do not impart to their “emergence” such linguistic certainty).
The bonds are financial instruments issued by these foreign govern-
ments, mostly Russia, Mexico, Brazil, Argentina, and Turkey. These
bonds traded for pennies when these governments were not doing well.
Suddenly investors rushed into these markets in the early 1990s and
pushed the envelope further and further by acquiring increasingly more
exotic securities. All these countries were building hotels where United
States cable news channels were available, with health clubs equipped
with treadmills and large-screen television sets that made them join the
global village. They all had access to the same gurus and financial
entertainers. Bankers would come to invest in their bonds and the
countries would use the proceeds to build nicer hotels so more investors
would visit. At some point these bonds became the vogue and went from
pennies to dollars; those who knew the slightest thing about them
accumulated vast fortunes.

Carlos supposedly comes from a patrician Latin-American family
that was heavily impoverished by the economic troubles of the 1980s,
but, again, I have rarely run into anyone from a ravaged country whose
family did not at some juncture own an entire province or, say, supply
the Russian Czar with sets of dominoes. After brilliant undergraduate
studies, he went to Harvard to pursue a Ph.D. in economics, as it was
the sort of thing Latin-American patricians had gotten into the habit of
doing at the time (with a view to saving their economies from the evils of
non-Ph.D. hands). He was a good student but could not find a decent
thesis topic for his dissertation. Nor did he gain the respect of his thesis
advisor, who found him unimaginative. Carlos settled for a Master’s
degree and a Wall Street career.

The nascent emerging market desk of a New York bank hired Carlos
in 1992. He had the right ingredients for success; he knew where on the
map to find the countries that issued “Brady bonds”, dollar-
denominated debt instruments issued by Less Developed Countries.
He knew what Gross Domestic Product meant. He looked serious,
brainy and well spoken, in spite of his heavy Spanish accent. He was the
kind of person banks felt comfortable putting in front of their
customers. What a contrast with the other traders who lacked polish!

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SOLON’S WARNING

Carlos got there right in time to see things happening in that market.
When he joined the bank, the market for emerging market debt
instruments was small and traders were located in undesirable parts of
trading floors. But the activity rapidly became a large, and growing, part
of the bank’s revenues.

He was generic among this community of emerging market traders;
they are a collection of cosmopolitan patricians from across the
emerging market world that remind me of the international coffee hour
at the Wharton School. I find it odd that rarely does a person specialize
in the market of his or her birthplace. Mexicans based in London trade
Russian securities, Iranians and Greeks specialize in Brazilian bonds,
and Argentines trade Turkish securities. Unlike my experience with real
traders, they are generally urbane, dress well, collect art, but are non-
intellectual. They seem too conformist to be true traders. They are
mostly between 30 and 40, owing to the youth of their market. You can
expect many of them to hold season tickets to the Metropolitan Opera.
True traders, I believe, dress sloppily, are often ugly and exhibit the
intellectual curiosity of someone who would be more interested in the
information-revealing contents of the garbage can than the Cezanne
painting on the wall.

Carlos thrived as a trader-economist. He had a large network of
friends in the various Latin-American countries and knew exactly what
took place there. He bought bonds that he found attractive, either
because they paid him a good rate of interest, or because he believed
that they would become more in demand in the future, therefore
appreciating in price. It would be perhaps erroneous to call him a trader.
A trader buys and .sells (he may sell what he does not own and buy it
back later, hopefully making a profit in a decline; this is called
“shorting”). Carlos just bought - and he bought in size. He believed that
he was paid a good risk premium to hold these bonds because there was
economic value in lending to these countries. Shorting, in his opinion,
made no economic sense.

Within the bank Carlos was the emerging markets reference. He
could produce the latest economic figures at the drop of a hat. He had
frequent lunches with the chairman. In his opinion, trading was
economics, little else. It had worked so well for him. He got promotion
after promotion, until he became the head trader of the emerging market

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SURVIVAL OF THE LEAST FIT

desk at the institution. Starting in 1995, Carlos did exponentially well in
his new function, getting an expansion of his capital on a steady basis
(i.e., the bank allocated a larger portion of its funds to his operation) -
so fast that he was incapable of using up the new risk limits.

THE GOOD YEARS

The reason Carlos had good years was not just because he bought
emerging market bonds and their value went up over the period. It was
mostly because he also bought dips. He accumulated when prices
experienced a momentary panic. The year 1997 would have been a bad
year had he not added to his position after the dip in October that
accompanied the false stock market crash that took place then.
Overcoming these small reversals of fortune made him feel invincible.
He could do no wrong. He believed that the economic intuition he was
endowed with allowed him to make good trading decisions. After a
market dip he would verify the fundamentals, and, if they remained
sound, he would buy more of the security and lighten up as the market
recovered. Looking back at the emerging market bonds between the
time Carlos started his involvement with these markets and his last
bonus check in December 1997, one sees an upward sloping line, with
occasional blips, such as the Mexican devaluation of 1995, followed by
an extended rally. One can also see some occasional dips that turned out
to be “excellent buying opportunities”.

It was the summer of 1998 that undid Carlos - that last dip did not
translate into a rally. His track record today includes just one bad
quarter - but bad it was. He had earned close to $80 million
cumulatively in his previous years. He lost $300 million in just one
summer. What happened? When the market started dipping in June, his
friendly sources informed him that the sell-off was merely the result of a
“liquidation” by a New Jersey hedge fund run by a former Wharton
professor. That fund specialized in mortgage securities and had just
received instructions to wind down the overall inventory. The inventory
included some Russian bonds, mostly because yield bogs , as these funds
are known, engage in the activity of building a “diversified” portfolio of
high-yielding securities.

72

SOLON’S WARNING

AVERAGING DOWN

When the market started falling, he accumulated more Russian bonds,
at an average of around $52. That was Carlos’s trait, average down. The
problems, he deemed, had nothing to do with Russia, and it was not
some New Jersey fund run by some mad scientist that was going to
decide the fate of Russia. “Read my lips: It’s a li-qui-da-tion!” he yelled
at those who questioned his buying.

By the end of June, his trading revenues for 1998 had dropped from
up $60 million to up $20 million. That made him angry. But he
calculated that should the market rise back to the pre-New Jersey sell-
off, then he would be up $100 million. That was unavoidable, he
asserted. These bonds, he said, would never, ever trade below $48. He
was risking so little, to possibly make so much.

Then came July. The market dropped a bit more. The benchmark
Russian bond was now at $43. His positions were under water, but he
increased his stakes. By now he was down $30 million for the year. His
bosses were starting to become nervous, but he kept telling them that, after
all, Russia would not go under. He repeated the cliche that it was too big
to fail. He estimated that bailing them out would cost so little and would
benefit the world economy so much that it did not make sense to liquidate
his inventory now. “This is the time to buy, not to sell”, he said repeatedly.
“These bonds are trading very close to their possible default value”. In
other words, should Russia go into default, and run out of dollars to pay
the interest on its debt, these bonds would hardly budge. Where did he get
this idea? From discussions with other traders and emerging market
economists (or trader-economist hybrids). Carlos put about half his net
worth, then $5,000,000, in the Russia Principal Bond. “I will retire on
these profits”; he told the stockbroker who executed the trade.

LINES IN THE SAND

The market kept going through the lines in the sand. By early August,
they were trading in the 30s. By the middle of August, they were in the
20s. And he was taking no action. He felt that the price on the screen
was quite irrelevant in his business of buying “value”.

SURVIVAL OF THE LEAST FIT

73

Signs of battle fatigue were starting to show in his behavior. Carlos
was getting jumpy and losing some of his composure. He yelled at
someone in a meeting: “stop losses are for schmucks! I am not going to
buy high and sell low!” During his string of successes he had learned to
put down and berate traders of the non-emerging market variety. “Had
we gotten out in October 1997 after our heavy loss we would not have
had those excellent 1997 results”, he was also known to repeat. He also
told management: “these bonds trade at very depressed levels. Those
who can invest now in these markets would realize wonderful returns”.
Every morning, Carlos spent an hour discussing the situation with
market economists around the globe. They all seemed to present a
similar story: this sell-off is overdone.

Carlos’s desk experienced losses in other emerging markets as well.
He also lost money in the domestic Russian Ruble Bond market. His
losses were mounting, but he kept telling his management rumors about
very large losses among other banks - larger than his. He felt justified to
show that “he fared well relative to the industry”. This is a symptom of
systemic troubles; it shows that there was an entire community of
traders who were conducting the exact same activity. Such statements,
that other traders had also gotten into trouble, are self-incriminating. A
trader’s mental construction should direct him to do precisely what
other people do not do.

Towards the end of August, the bellwether Russia Principal Bonds
were trading below $10. Carlos’s net worth was reduced by almost half.
He was dismissed. So was his boss, the head of trading. The president of
the bank was demoted to a “newly created position”. Board members
could not understand why the bank had so much exposure to a govern-
ment that was not paying its own employees - which, disturbingly,
included armed soldiers. This was one of the small points that emerging
market economists around the globe, from talking to each other so
much, forgot to take into account. Veteran trader Marty O’Connell calls
this the firehouse effect. He had observed that firemen with much
downtime who talk to each other for too long come to agree on many
things that an outside, impartial observer, would find ludicrous (they
develop political ideas that are very similar). Psychologists give it a
fancier name, but my friend Marty has no training in clinical
psychology.

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SOLON’S WARNING

The nerdy types at the International Monetary Fund had been taken
for a ride by the Russian government who cheated on their account. Let
us remember that economists are evaluated on how intelligent they
sound, not on a scientific measure of their knowledge of reality. How-
ever, the price of the bonds was not fooled. It knew more than the
economists, more than the Carloses of the emerging market departments.

Louie, a veteran trader on the neighboring desk who suffered much
humiliation by these rich emerging market traders, was there, vindicated.
Louie was then a 52-year-old Brooklyn-born-and-raised trader who over
three decades survived every single conceivable market cycle. He calmly
looked at Carlos being escorted by a security guard to the door like a
captured soldier taken to the arena. He muttered in his Brooklyn accent:
“Economics Schmeconomics. It is all market dynamics

Carlos is now out of the market. The possibility that history may
prove him right (at some point in the future) has nothing to do with the
fact that he is a bad trader. He has all of the traits of a thoughtful
gentleman, and would be an ideal son-in-law. But he has most of the
attributes of the bad trader. And, at any point in time, the richest traders
are often the worst traders. This, I will call the cross-sectional problem:
at a given time in the market, the most profitable traders are likely to be
those that are best fit to the latest cycle. This does not happen too often
with dentists or pianists - because of the nature of randomness.

John the High-Yield Trader

We met John, Nero’s neighbor, in Chapter 1. At the age of 35 he had
been on Wall Street as a corporate “high-yield” bonds trader for seven
years, since his graduation from Pace Graduate Business School. He rose
to head up a team of ten traders in record time - thanks to a jump
between two similar Wall Street firms that afforded him a generous
profit-sharing contract. The contract allowed him to be paid 20% of his
profits, as they stood at the end of each calendar year. In addition, he
was allowed to invest his own personal money in his trades - a great
privilege.

SURVIVAL OF THE LEAST FIT

75

John is not someone who can be termed as principally intelligent, but
he was believed to be endowed with a good measure of business sense.
He was said to be “pragmatic” and “professional”. He gave the
impression that he was born a businessperson, never saying anything
remotely unusual or out of place. He remained calm in most
circumstances, rarely betraying any form of emotion. Even his
occasional cursing (this is Wall Street!) was so much in context that it
sounded, well, professional.

John dressed impeccably. This was in part due to his monthly trips to
London where his unit had a satellite supervising European high-yield
activities. He wore a Saville Row tailored dark business suit, with a
Ferragamo tie - enough to convey the impression that he was the
epitome of the successful Wall Street professional. Each time Nero ran
into him he came away feeling poorly dressed.

John’s desk engaged principally in an activity called “high-yield”
trading, which consisted in acquiring “cheap” bonds that yielded, say
10%, while the borrowing rate for his institution was 5.5%. It netted a
4.5% revenue, also called interest rate differential - which seemed small
except that he could leverage himself and multiply such profit by the
leverage factor. He did this in various countries, borrowing at the local
rate and investing in “risky” assets. It was easy for him to amass over $3
billion dollars in face value of such trade across a variety of continents.
He hedged the interest rate exposure by selling U.S., U.K., French, and
other government bond futures, thus limiting his bet to the differential
between the two instruments. He felt protected by this hedging strategy
- cocooned (or so he thought) against those nasty fluctuations in the
world’s global interest rates.

THE QUANT WHO KNEW COMPUTERS AND EQUATIONS

John was assisted by Henry, a foreign quant whose English was
incomprehensible, but who was believed to be at least equally
competent in risk-management methods. John knew no math, he relied
on Henry. “His brains and my business sense”, he was wont to say.
Henry supplied him with risk assessments concerning the overall
portfolio. Whenever John felt worried, he would ask Henry for another

76

SOLON’S WARNING

freshly updated report. Henry was a graduate student in Operations
Research when John hired him. His specialty was a field called
Computational Finance, which, as its name indicates, seems to focus
solely on running computer programs overnight. Henry’s income went
from $50,000 to $600,000 in three years.

Most of the profit John generated for the institution was not
attributable to the interest rate differential between the instruments
described above. It came from the changes in the value of the securities
John held, mostly because many other traders were acquiring them to
imitate John’s trading strategy (thus causing the price of these assets to
rise). The interest rate differential was getting closer to what John
believed was “fair value”. John believed that the methods he used to
calculate “fair value” were sound. He was backed by an entire
department that helped him analyze and determine which bonds were
attractive and offered capital appreciation potential. It was normal for
him to be earning these large profits over time.

John made steady money for his employers, perhaps even better than
steady. Every year the revenues he generated almost doubled as com-
pared to the previous year. During his last year, his income experienced a
quantum leap as he saw the capital allocated to his trades swell beyond
his wildest expectations. His bonus check was for $10 million (pretax,
which would generate close to a $5 million total tax bill). John’s personal
net worth reached $1 million at the age of 32. By the age of 35 it had
exceeded $16 million. Most of it came from the accumulation of bonuses
- but a sizeable share came from profits on his personal portfolio. Of the
$16 million, about $14 million he insisted in keeping invested in his
business. They allowed him, thanks to the leverage (i.e., use of borrowed
money), to keep a portfolio of $50 million involved in his trades, with
$36 million borrowed from the bank. The effect of the leverage is that a
small loss would be compounded and would wipe him out.

It took only a few days for the $14 million to turn into thin air - and
for John to lose his job at the same time. It all happened during the
summer of 1998, with the meltdown of high-yield bond values. Markets
went into a volatile phase in which nearly everything he had invested in
went against him at the same time. His hedges no longer worked out. He
was mad at Henry for not having figured out that these events could
happen. Perhaps there was a bug in the program.

SURVIVAL OF THE LEAST FIT

77

His reaction to the first losses was, characteristically, to ignore the
market. “One would go crazy if one were to listen to the mood swings of
the market”, he said. What he meant by that statement was that the “noise”
was mean reverting, and would likely be offset by “noise” in the opposite
direction. That was the translation in plain English of what Henry
explained to him. But the “noise” kept adding up in the same direction.

As in a biblical cycle, it took seven years to make John a hero and just
seven days to make him an idiot. John is now a pariah; he is out of a job
and his telephone calls are not returned. Many of his friends were in the
same situation. How? With all that information available to him, his
perfect track record (and therefore, in his eyes, an above average
intelligence and skill-set) and the benefit of sophisticated mathematics,
how could he have failed? Is it perhaps possible that he forgot about the
shadowy figure of randomness?

It took a long time for John to figure out what had happened,
owing to the rapidity with which the events unfolded and his state of
shellshock. The dip in the market was not very large. It was just
that his leverage was enormous. What was more shocking for him
was that all their calculations gave the event a probability of 1 in
1,000,000,000,000,000,000,000,000 years. Henry called that a “ten
sigma” event. The fact that Henry doubled the odds did not seem to
matter. It made the probability 2 in 1,000,000,000,000,000,000,000,000
years.

When will John recover from the ordeal? Probably never. The reason
is not because John lost money. Losing money is something good traders
are accustomed to. It is because he blew up; he lost more than he
planned to lose. His personal confidence was wiped out. But there is
another reason why John may never recover. The reason is that John
was never a trader in the first place. He is one of those people who
happened to be there when it all happened.

Following the incident, John regarded himself “ruined”; yet his net
worth is still close to $1 million, which could be the envy of more than
99.9% of the inhabitants of our planet. Yet there is a difference between
a wealth level reached from above and a wealth reached from below.
The road from $16 million to $1 million is not as pleasant as the one
from 0 to $1 million. In addition, John is full of shame; he still worries
about running into old friends on the street.

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SOLON’S WARNING

His employer should perhaps be most unhappy with the overall
outcome. John pulled some money out of the episode, the $1 million he
had saved. He should be thankful that the episode did aot cost him
anything - except the emotional drain. His net worth did not become
negative. That was not the case for his last employer. John had earned
for the employers, New York investment banks, around $250 million in
the course of the seven years. He lost more than $600 million for his last
employer in barely a few days.

THE TRAITS THEY SHARED

The reader needs to be warned that not all of the emerging market and
high-yield traders talk and behave like Carlos and John. Only the most
successful ones - alas, or perhaps those who were the most successful
during the 1992-1998 bull cycle.

At their age, both John and Carlos still have the chance to make a
career. It would be wise for them to look outside of the financial
markets. The odds are that they will not survive the incident. Why?
Because by discussing the situation with each of them, one can rapidly
see that they share the traits of the acute successful randomness fool.
What is more worrisome is that their bosses and employers shared the
same trait. They, too, are permanently out of the market. We will see
throughout this book what characterizes the trait. Again, there may not
be a clear definition for it, but you can recognize it when you see it. No
matter what John and Carlos do, they will remain fools of randomness.

A Review of Market Fools of Randomness
Constants

Most of the traits partake of the same Table P.l right-column-left-
column confusion; how they are fooled by randomness. Below is a brief
outline of them:

SURVIVAL OF THE LEAST FIT

79

An over estimation of the accuracy of their beliefs in some measure,
either economic (Carlos) or statistical (John). They never con-
sidered that the fact that trading on economic variables has worked
in the past may have been merely coincidental, or, perhaps even
worse, that economic analysis was fit to past events to mask the
random element in it. Carlos entered the market at a time when it
worked, but he never tested for periods when markets did the
opposite of sound economic analysis. There were periods when
economics failed traders, and others when it helped them.

The U.S. dollar was overpriced (i.e. the foreign currencies were
undervalued) in the early 1980s. Traders who used their economic
intuitions and bought foreign currencies were wiped out. But later
those who did so got rich (members of the first crop were bust). It is
random! Likewise, those who “shorted” Japanese stocks in the late
1980s suffered the same fate - few survived to recoup their losses
during the collapse of the 1990s. At the time of writing, there is a
group of operators called “macro” traders who are dropping like
flies, with “legendary” (rather, lucky) investor Julian Robertson
closing shop in 2000 after having been a star until then. Our
discussion of survivorship bias will enlighten us further, but, clearly,
there is nothing less rigorous than their seemingly rigorous use of
economic analysis to trade.

A tendency to get married to positions. There is a saying that bad
traders divorce their spouse sooner than abandon their positions.
Loyalty to ideas is not a good thing for traders, scientists - or
anyone.

The tendency to change their story. They become investors “for the
long haul” when they are losing money, switching back and forth
between traders and investors to fit recent reversals of fortune. The
difference between a trader and an investor lies in the duration of the
bet, and the corresponding size. There is absolutely nothing wrong
with investing “for the long haul”, provided one does not mix it with
short-term trading - it is just that many people become long-term
investors after they lost money, postponing their decision to sell, as
part of their denial.

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SOLON’S WARNING

No precise game plan ahead of time as to what to do in the event of
losses. They simply were not aware of such a possibility. Both
bought more bonds after the market declined sharply,, but not in
response to a predetermined plan.

Absence of critical thinking expressed in absence of revision of their
stance with “stop losses”. Middlebrow traders do not like selling
when it is “even better value”. They did not consider that perhaps
their method of determining value is wrong, rather than the market
failing to accommodate their measure of value. They may be right,
but, perhaps, some allowance for the possibility of their methods
being flawed was not made. For all his flaws, we will see that Soros
seems rarely to examine an unfavorable outcome without testing his
own framework of analysis.

Denial. When the losses occurred there was no clear acceptance of
what had happened. The price on the screen lost its reality in favor of
some abstract “value”. In classic denial mode, the usual “this is only
the result of liquidation, distress sales” was proffered. They
continuously ignored the message from reality.

How could traders who made every single mistake in the book become
so successful? Because of a simple principle concerning randomness.
This is one manifestation of the survivorship bias. We tend to think that
traders make money because they are good. Perhaps we have turned the
causality on its head; we consider them good just because they make
money. One can make money in the financial markets totally out of
randomness. '■

Both Carlos and John belong to the class of people who benefited
from a market cycle. It was not merely because they were involved in the
right markets. It was because they had a bent in their style that closely
fitted the properties of the rallies experienced in their market during the
episode. They were dip buyers. That happened, in hindsight, to be the
trait that was the most desirable between 1992 and the summer of 1998
in the specific markets in which the two men specialized. Most of those
who happened to have that specific trait, over the course of that segment
of history, dominated the market. Their score was higher and they
replaced people who, perhaps, were better traders.

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81

Naive Evolutionary Theories

This story illustrates how bad traders have a short- and medium-term
survival advantage over good traders. Next we take the argument to a
higher level of generality. One must be either blind or foolish to reject
the theories of Darwinian self-selection. However, the simplicity of the
concept has drawn segments of amateurs (as well as a few professional
scientists) into blindly believing in continuous and infallible Darwinism
in all fields, which includes economics.

The biologist Jacques Monod bemoaned a couple of decades ago that
everyone believes himself an expert on evolution (the same can be said
about the financial markets); things have gotten worse. Many amateurs
believe that plants and animals reproduce on a one-way route towards
perfection. Translating the idea in social terms, they believe that
companies and organizations are, thanks to competition (and the
discipline of the quarterly report), irreversibly heading towards
betterment. The strongest will survive; the weakest will become extinct.
As to investors and traders, they believe that by letting them compete,
the best will prosper and the worst will go learn a new craft (like
, pumping gas or, sometimes, dentistry).

Things are not as simple as that. We will ignore the basic misuse of
Darwinian ideas in the fact that organizations do not reproduce like living
members of nature - Darwinian ideas are about reproductive fitness, not
about survival. The problem comes, as everything else in this book, from
randomness. Zoologists found that once randomness is injected into a
system, the results can be quite surprising: what seems to be an evolution
may be merely a diversion, and possibly regression. For instance, Steven Jay
Gould (admittedly more of a popularizer than a genuine scientist) found
ample evidence of what he calls “genetic noise”, or “negative mutations”,
, thus causing the wrath of some of his colleagues (he took the idea a little
too far). An academic debate ensued, plotting Gould against colleagues like
Dawkins who were considered by their peers as better trained in the
mathematics of randomness. Negative mutations are traits that survive in
spite of being worse, from the reproductive fitness standpoint, than the
ones they replaced. However, they cannot be expected to last more than a
few generations (under what is called temporal aggregation).

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SOLON’S WARNING

Furthermore, things can get even more surprising when randomness
changes in shape, as with regime switches. A regime switch corresponds
to situations when all of the attributes of a system change to the point of
it becoming unrecognizable to the observer. Darwinian fitness applies to
species developing over a very long time, not observed over a short term
- time aggregation eliminates much of the effects of randomness; things
(I read noise) balance out over the long run, as people say.

Owing to the abrupt rare events, we do not live in a world where
things “converge” continuously towards betterment. Nor do things in
life move continuously at all. The belief in continuity was ingrained in
our scientific culture until the early twentieth century. It was said that
nature does not make jumps ; people quote this in well-sounding Latin:
natura no facit saltus. It is generally attributed to the eighteenth-century
botanist Linnaeus who obviously got it all wrong. It was also used by
Leibniz as a justification of calculus, as he believed that things are
continuous no matter the resolution at which we look at them. Like
many well-sounding “make sense” types of statements (such dynamics
made perfect intellectual sense), it turned out to be entirely wrong, as it
was denied by quantum mechanics. We discovered that, in the very
small, particles jump (discretely) between states; they do not slide
between them.

CAN EVOLUTION BE FOOLED BY RANDOMNESS?

We end this chapter with the following thought. Recall that someone
with only casual knowledge about the problems of randomness would
believe that an animal is at the maximum fitness for the conditions of his
time. This is not what evolution means; on average animals will be fit,
but not every single one of them, and not at all times. Just as an animal
could have survived because its sample path was lucky, the “best”
operators in a given business can come from - a subset of operators who
survived because of over-fitness to a sample path - a sample path that
was free of the evolutionary rare event. One vicious attribute is that the
longer these animals can go without encountering the rare event, the
more vulnerable they will be to it. We said that should one extend time
to infinity, then, by ergodicity, that event will happen with certainty -

SURVIVAL OF THE LEAST FIT

83

the species will be wiped out! For evolution means fitness to one and
only time series, not the average of all the possible environments.

By some viciousness of the structure of randomness, a profitable
person like John, someone who is a pure loser in the long run and
correspondingly unfit for survival, presents a high degree of eligibility in
the short run and has the propensity to multiply his genes. Recall the
hormonal effect on posture and its signaling effect to other potential
mates. His success (or pseudo-success owing to its fragility) will show in
his features as a beacon. An innocent potential mate will be fooled into
thinking (unconditionally) that he has a superior genetic makeup, until
the following rare event. Solon seems to have gotten the point; but try to
explain the problem to a naive business Darwinist - or your rich
neighbor across the street.

We introduce the concept of skewness: why the terms “bull" and
“bear” have limited meaning outside of zoology. A vicious child
wrecks the structure of randomness. An introduction to the
problem of epistemological opacity. The penultimate step
before the problem of induction.

The Median Is Not the Message

T he writer and scientist Steven Jay Gould (who, for a while, was my
role model), was once diagnosed with a deadly form of cancer of
the lining of the stomach. The first piece of information he received
about his odds of making it was that the median survival for the ailment
is approximately eight months; information he felt akin to Isaiah’s
injunction to King Hezekiah to put his house in order in preparation for
death.

Now a medical diagnosis, particularly one of such severity, can
motivate people to do intensive research, particularly those prolific
writers like Gould who needed more time with us to complete a few
book projects. The further research by Gould uncovered a very different

SKEWNESS AND ASYMMETRY

85

story to the information he had initially been given; mainly that the
expected (i.e., average) survival was considerably higher than eight
months. It came to his notice that expected and median do not mean the
same thing at all. Median means roughly that 50% of the people die
before eight months and 50% survive longer than eight months. But
those who survive would live considerably longer, generally going about
life just like a regular person and fulfilling the average 73.4 or so years
predicted by insurance mortality tables.

There is asymmetry. Those who die do so very early in the game,
while those who live go on living very long. Whenever there is
asymmetry in outcomes, the average survival has nothing to do with the
median survival. This prompted Gould, who thus discovered the
concept of skewness, to write his heartfelt piece “The Median is Not
the Message”. His point is that the concept of median used in medical
research does not characterize a probability distribution.

I will simplify Gould’s point by introducing the concept of mean (also
called expectation) as follows by using a less morbid example, that of
gambling. I will give an example of both asymmetric odds and
asymmetric outcomes to explain the point. Asymmetric odds means
that probabilities are not 50% for each event, but that the probability
on one side is higher than the probability on the other. Asymmetric
outcomes mean that the payoffs are not equal.

Assume I engage in a gambling strategy that has 999 chances in 1,000
of making $1 (event A) and 1 chance in 1,000 of losing $10,000 (event
B), as in Table 6.1.

Table 6.1

Event

Probability

Outcome

Expectation

A

99 9/1000

$1

$.999

B

1/1000

-$10.00

Total

-$9,001

My expectation is a loss of close to $9 (obtained by multiplying the
probabilities by the corresponding outcomes). The frequency or
probability of the loss, in and by itself, is totally irrelevant; it needs to
be judged in connection with the magnitude of the outcome. Here A is

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SOLON’S WARNING

far more likely than B. Odds are that we would make money by betting
for event A, but it is not a good idea to do so.

This point is rather common and simple; it is understood by anyone
making a simple bet. Yet I had to struggle all my life with people in the
financial markets who do not seem to internalize it. I am not talking of
novices; I am talking of people with advanced degrees (albeit MBAs)
who cannot come to grips with the difference.

How could people miss such a point? Why do they confuse
probability and expectation, that is, probability and probability times
the payoff? Mainly because much of people’s schooling comes from
examples in symmetric environments, like a coin-toss, where such a
difference does not matter. In fact the so-called “Bell Curve” that seems
to have found universal use in society is entirely symmetric. More on
that later.

Bull and Bear Zoology

The general press floods us with concepts like bullish and bearish as
these mean to refer to the effect of higher (bullish) or lower (bearish)
prices in the financial markets. But also we hear people saying “I am
bullish on Johnny” or “I am bearish on that guy Nassim in the back who
seems incomprehensible to me”, to denote the belief in the likelihood of
someone’s rise in life. I have to say that the notion bullish or bearish are
often hollow words with no application in a world of randomness -
particularly if such a world, like ours, presents asymmetric outcomes.

When I was in the employment of the New York office of a large
investment house, I was subjected on occasions to the harrying weekly
“discussion meeting”, which gathered most professionals of the New York
trading room. I do not conceal that I was not fond of such gatherings, and
not only because they cut into my gym time. While the meetings included
traders, that is, people who are judged on their numerical performance, it
was mostly a forum for salespeople (people capable of charming
customers), and the category of entertainers called Wall Street
“economists” or “strategists” who make pronouncements on the fate of

SKEWNESS AND ASYMMETRY

87

the markets, but do not engage in any form of risk taking, thus having their
success dependent on rhetoric rather than actually testable facts. During
the discussion, people were supposed to present their opinions on the state
of the world. To me, the meeting was pure intellectual pollution. Everyone
had a story, a theory, and insights that they wanted others to share. I resent
the person who, without having done much homework in libraries, thinks
that he is onto something rather original and insightful on a given subject
matter (and respect people with scientific minds like my friend Stan Jonas
who feel compelled to spend their nights reading wholesale on a subject
matter, trying to figure out what was done on the subject by others before
emitting an opinion - would the reader listen to the opinion of a doctor
who does not read medical papers?).

I have to confess that my optimal strategy (to soothe my boredom
and allergy to confident platitudes) was to speak as much as I could,
while totally avoiding listening to other people’s replies by trying to
solve equations in my head. Speaking too much would help me clarify
my mind, and, with a little bit of luck, I would not be “invited” back
(that is, forced to attend) the following week.

I was once asked in one of those meetings to express my views on the
stock market. I stated, not without a modicum of pomp, that I believed
that the market would go slightly up over the next week with a high
probability. How high? “About 70%”. Clearly, that was a very strong
opinion. But then someone interjected “But, Nassim, you just boasted
being short a very large quantity of SP500 futures, making a bet that the
market would go down. What made you change your mind?”. “I did not
change my mind! I have a lot of faith in my bet! (audience laughing). As
a matter of fact I now feel like selling even more!” The other employees
in the room seemed utterly confused. “Are you bullish or are you
bearish?” I was asked by the strategist. I replied that I could not
understand the words “bullish” and “bearish” outside of their purely
zoological consideration. Just as with events A and B in the preceding
example, my opinion was that the market was more likely to go up (“I
would be bullish”), but that it was preferable to short it (“I would be
bearish”), because, in the event of its going down, it could go down a
lot. Suddenly, the few traders in the room understood my opinion and
started voicing similar opinions. And I was not forced to come back to
the following discussion.

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SOLON’S WARNING

Let us assume that the reader shared my opinion, that the market
over the next week had a 70% probability of going up and 30%
probability of going down. However, let us say that it would _go up by
1% on average, while it could go down by an average of 10%. What
would the reader do? Is the reader bullish or is he bearish ?

Table 6.2

Event

Probability

Outcome

Expectation

Market goes up

70%

Up 1%

0.7

Market goes down

30%

Down 10%

-3.00

Total

-2.3

Accordingly, bullish or bearish are terms used by people who do not
engage in practicing uncertainty, like the television commentators, or
those who have no experience in handling risk. Alas, investors and
businesses are not paid in probabilities, they are paid in dollars.
Accordingly, it is not how likely an event is to happen that matters, it is
how much is made when it happens that should be the consideration. How
frequent the profit is irrelevant; it is the magnitude of the outcome that
counts. It is a pure accounting fact that, aside from the commentators,
very few people take home a check linked to how often they are right or
wrong. What they get is a profit or loss. As to the commentators, their
success is linked to how often they are right or wrong. This category
includes the “chief strategists” of major investment banks the public can
see on T.V., who are ‘nothing better than entertainers. They are famous,
seem reasoned in their speech, plow you with numbers, but, functionally,
they are there to entertain - for their predictions to have any validity they
would need a statistical testing framework. Their fame is not the result of
some elaborate test but rather the result of their presentation skills.

AN ARROGANT 29-YEAR-OLD SON

Outside of the need for entertainment in these shallow meetings I have
resisted voicing a “market call” as a trader, which caused some personal

SKEWNESS AND ASYMMETRY

89

strain with some of my friends and relatives. One day a friend of my
father - of the rich and confident variety - called me during his New
York visit (to set the elements of pecking order straight, he hinted right
away during the call that he came by Concorde, with some derogatory
comment on the comfort of such method of transportation). He wanted
to pick my brain on the state of a collection of financial markets. I truly
had no opinion, nor had made the effort to formulate any, nor was I
remotely interested in markets. The gentleman kept plowing me with
questions on the state of economies, on the European central banks;
these were precise questions no doubt aiming to compare my opinion to
that of some other “expert” handling his account at one of the large
New York investment firms. I neither concealed that I had no clue, nor
did I seem sorry about it. I was not interested in markets (“yes, I am a
trader”) and did not make predictions, period. I went on to explain to
him some of my ideas on the structure of randomness and the
verificability of market calls but he wanted a more precise statement
of what the European bond markets would do by the Christmas season.

He came under the impression that I was pulling his leg; it almost
damaged the relationship between my father and his rich and confident
friend. For the gentleman called him with the following grievance:
“When I ask a lawyer a legal question, he answers me with courtesy and
precision. When I ask a doctor a medical question, he gives me his
opinion. No specialist ever gives me disrespect. Your insolent and
conceited 29-year-old son is playing prima donna and refuses to answer
me about the direction of the market!”

RARE EVENTS

The best description of my lifelong business in the market is “skewed
bets”, that is, I try to benefit from rare events, events that do not tend to
repeat themselves frequently, but, accordingly, present a large payoff
when they occur. I try to make money infrequently, as infrequently as
possible, simply because I believe that rare events are not fairly valued,
and that the rarer the event, the more undervalued it will be in price.

Why? Because of a psychological bias; people who surrounded me in
my career were too focused on memorizing section 2 of the Wall Street

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Journal during their train ride to reflect properly on the attributes of
random events. Or perhaps they watched too many gurus on television.
Or perhaps they spent too much time upgrading their PalmPilot. Even
some experienced trading veterans do not seem to get the point that
frequencies do not matter. Jim Rogers, a “legendary” investor, made the
following statement:

I don’t buy options. Buying options is another way to go to the poor-
house. Someone did a study for the SEC and discovered that 90 percent
of all options expire as losses. Well, I figured out that if 90 percent of all
long option positions lost money, that meant that 90 percent of all short
option positions make money. If I want to use options to be bearish, I
sell calls.

Visibly, the statistic that 90% of all option positions lost money is
meaningless, (i.e., the frequency) if we do not take into account how
much money is made on average during the remaining 10%. If we make
50 times our bet on average when the option is in the money, then I can
safely make the statement that buying options is another way to go to
the palazzo rather than the poorhouse. Mr Jim Rogers seems to have
gone very far in life for someone who does not distinguish between
probability and expectation (strangely, he was the partner of George
Soros, a complex man who thrived on rare events - more on him later).

One such rare event is the stock market crash of 1987, which made
me as a trader and allowed me the luxury of becoming involved in all
manner of scholarship. Nero of the smaller house in Chapter 1 aims to
get out of harm’s way by avoiding exposure to rare events - a mostly
defensive approach. I am far more aggressive than Nero and go one step
further; I have organized my career and business in such a way as to be
able to benefit from them. In other words, I aim at profiting from the
rare event, with my asymmetric bets.

SYMMETRY AND SCIENCE

In most disciplines, such asymmetry does not matter. Unfortunately, the
techniques used in finance are often imported from other areas - finance

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91

is still a young discipline (it is certainly not yet a “science”). People in
most fields outside of finance do not have problems eliminating extreme
values from their sample, when the difference in payoff between
different outcomes is not significant, which is generally the case in
education and medicine. A professor who computes the average of his
students’ grades removes the highest and lowest observations, which he
would call outliers, and takes the average of the remaining ones,
without this being an unsound practice. A casual weather forecaster
does the same with extreme temperatures - an unusual occurrence might
be deemed to skew the overall result (though we will see that this may
turn out to be a mistake when it comes to forecasting future properties
of the ice cap). So people in finance borrow the technique and ignore
infrequent events, not noticing that the effect of a rare event can
bankrupt a company.

Many scientists in the physical world are also subject to such
foolishness, misreading statistics. One flagrant example is in the global-
warming debate. Many scientists failed to notice it in its early stages as
they removed from their sample the spikes in temperature, under the
belief that these were not likely to recur. It may be a good idea to take
out the extremes when computing the average temperatures for vacation
scheduling. But it does not work when we study the physical properties
of the weather. These scientists initially ignored the fact that these
spikes, although rare, had the effect of adding disproportionately to the
cumulative melting of the ice cap. Just as in finance, an event, although
rare, that brings large consequences cannot just be ignored.

Figure 6.1 shows a series of points starting with an initial level W 0
and ending at the period concerned W t . It can also be seen as the
performance, hypothetical or realized, of your favorite trading strategy,
the track record of an investment manager, the price of a foot of average
Palazzo real estate in Renaissance Florence, the price series of the
Mongolian stock market, or the difference between the U.S. and
Mongolian stock markets. It is composed of a given number of
sequential observations Wi, W 2 , etc., ordered in such a way that the one
to the right comes after the one to the left.

If we were dealing with a deterministic world - that is, a world
stripped of randomness (the right-column world in Table P.l on page 3),
and we knew with certainty that it was the case, things would be rather

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easy. The pattern of the series would reveal considerable and predictive
information. You could tell with precision what would happen one day
ahead, one year ahead, and perhaps even a decade ahead. We would not
even need a statistician; a second-rate engineer would do. He does not
even need to be armed with a modern degree; someone with nineteenth-
century training under Laplace would be able to solve the equations,
called differential equations , or, equivalently, equations of motion -
since we are studying the dynamics of an entity whose position depends
on time.

If we were dealing with a world where randomness is charted, things
would be easy as well, given that there is an entire field created for that
called Econometrics or Time Series Analysis. You would call a friendly
econometrician (my experience of econometricians is that they are
usually polite and friendly to practitioners). He would run the data in
his software, and prdvide you with diagnostics that would tell you if it is
worth investing in the trader generating such a track record, or if it is
worth pursuing the given trading strategy. You can even buy the student
version of his software for under $999 and run it yourself during the
next rainy weekend.

But we are not sure that the world we live in is well charted. We will
see that the judgment derived from the analysis of these past attributes
may on occasion be relevant. But it may be meaningless; it could on
occasion mislead you and take you in the opposite direction. Sometimes
market data becomes a simple trap; it shows you the opposite of its
nature, simply to get you to invest in the security or mismanage your

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risks. Currencies that exhibit the largest historical stability, for example,
are the most prone to crashes. This was bitterly discovered in the
summer of 1997 by investors who chose the safety of the pegged
currencies of Malaysia, Indonesia, and Thailand (they were pegged to
the U.S. dollar in a manner to exhibit no volatility, until their sharp,
sudden, and brutal devaluations).

We could be either too lax or too stringent in accepting past infor-
mation as a prediction of the future. As a skeptic, I reject a sole time
series of the past as an indication of future performance; I need a lot
more than data. My major reason is the rare event , but I have plenty of
others.

On the surface, my statement here may seem to contradict earlier
discussions, where I blame people for not learning enough from history.
The problem is that we read too much into shallow recent history, with
statements like “this has never happened before”, but not from history
in general (things that never happened before in one area tend eventually
to happen). In other words history teaches us that things that never
happened before do happen. It can teach us a lot outside of the narrowly
defined time series; the broader the look, the better the lesson. In other
words, history teaches us to avoid the brand of naive empiricism that
consists of learning from casual historical facts.

The Rare Event Fallacy

THE MOTHER OF ALL DECEPTIONS

The rare event, owing to its dissimulative nature, can take a variety of
shapes. It is in Mexico that it was spotted first, where it was called by
academics the peso problem. Econometricians were puzzled by the
behavior of the Mexican economic variables during the 1980s. The money
supply, interest rates, or some similar measure of small relevance to the
story exhibited some moody behavior, thwarting many of their efforts at
modeling them. These indicators erratically switched between periods of
stability to brief bursts of turbulence without warning.

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By generalization, I started to label a rare event as any behavior where
the adage “beware of calm waters” can hold. Popular wisdom often
warns of the old neighbor who appears to remain courtly and reserved,
the model of an excellent citizen, until you see his picture in the national
paper as a deranged killer who went on a rampage. Until then, he was not
known to have committed any transgression. There was no way to
predict that such pathological behavior could emanate from such a nice
person. I associate rare events with any misunderstanding of the risks
derived from a narrow interpretation of past time series.

Rare events are always unexpected, otherwise they would not occur.
The typical case is as follows. You invest in a hedge fund that enjoys
stable returns and no volatility, until one day, you receive a letter
starting with “An unforeseen and unexpected event, deemed a rare
occurrence ...” (emphasis mine). But rare events exist precisely because
they are unexpected. They are generally caused by panics, themselves
the results of liquidations (the investors rushing to the door
simultaneously by dumping anything they can put their hands on as
fast as possible). If the fund manager or trader expected it, he and his
like-minded peers would not have invested in it, and the rare event
would not have taken place.

The rare event is not limited to one security. It can readily affect the
performance of a portfolio. For example, many traders engage in the
purchase of mortgage securities and hedge them in some manner to
offset the risks and eliminate the volatility, hoping to derive some profits
in excess of the Treasury bond returns (which is used as the benchmark
of the minimum expected returns on an investment). They use computer
programs and draw meaningful assistance from Ph.D.s in applied
mathematics, astrophysics, particle physics, electrical engineering, fluid
dynamics, or sometimes (though rarely) plain Ph.D.s in Finance. Such a
portfolio shows stable returns for long periods. Then, suddenly, as if by
accident (I consider that no accident), the portfolio drops by 40% of its
value when you expect, at the worst, a 4% drop. You call the manager
to express your anger and he tells you that it was not his fault, but
somehow the relationship dramatically changed (literally). He will also
point out to you that similar funds also experienced the same problems.

Recall that some economists call the rare event a “peso problem”.
The designation peso problem does not appear to be undeservedly

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stereotypical. Things have not gotten better since the early 1980s with
the currency of the U.S.’s southern neighbor. Long periods of stability
draw hordes of bank currency traders and hedge fund operators to the
calm waters of the Mexican peso; they enjoy owning the currency
because of the high interest rate it commands. Then they “unexpectedly”
blow up, lose money for investors, lose their jobs and switch careers.
Then a new period of stability sets in. New currency traders come in
with no memory of the bad event. They are drawn to the Mexican peso,
and the story repeats itself.

It is an oddity that most fixed income financial instruments present
rare events. In the spring of 1998, I spent two hours explaining to a
then-important hedge fund operator the notion of the peso problem. I
went to great lengths to explain to him that the concept was generalized
to every form of investment that was based on a naive interpretation of
the volatility of past time series. The reply was: “You are perfectly right.
We do not touch the Mexican peso. We only invest in the Russian
ruble”. He blew up a few months later. Until then, the Russian ruble
carried attractive interest rates, which invited yield hogs of all types to
get involved. He and other holders of investments denominated in rubles
lost close to 97% of their investment during the summer of 1998.

We saw in Chapter 3 that the dentist does not like volatility as it
causes a high incidence of negative pangs. The closer he observes his
performance, the more pain he will experience owing to the greater
variability at a higher resolution. Accordingly investors, merely for
emotional reasons, will be drawn into strategies that experience rare but
large variations. It is called pushing randomness under the rug.

We can look at other aspects of the problem; think of someone
involved in scientific research. Day after day, he will engage in dissecting
mice in his laboratory, away from the rest of the world. He could try
and try for years and years without anything to show for it. His
significant other might lose patience with the loser who comes home
every night smelling of mice urine. Until bingo, one day he comes up
with a result. Someone observing the time series of his occupation would
see absolutely no gain, while every day would bring him closer in
probability to the end result.

The same with publishers; they can publish dog after dog without
their business model being the least questionable, if once every decade

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they hit on a Harry Potter string of super-best-sellers - provided of
course that they publish quality work that has a small probability of
being of very high appeal.

In the markets, there is a category of traders who have inverse rare
events, for whom volatility is often a bearer of good news. These traders
lose money frequently, but in small amounts, and make money rarely,
but in large amounts. I call them crisis hunters. I am happy to be one of
them.

WHY DON’T STATISTICIANS DETECT RARE EVENTS?

Statistics to the layman can appear rather complex, but the concept
behind what is used today is so simple that my French mathematician
friends call it deprecatorily “cuisine”. It is all based on one simple
notion; the more information you have, the more you are confident
about the outcome. Now the problem; by how much? Common
statistical method is based on the steady augmentation of the confidence
level, in nonlinear proportion to the number of observations. That is, for
an n times increase in the sample size, we increase our knowledge by the
square root of n. Suppose I am drawing from an urn containing red and
black balls. My confidence level about the relative proportion of red and
black balls, after 20 drawings is not twice the one I have after 10
drawings; it is merely multiplied by the square root of 2 (that is, 1.41).

Where statistics becomes complicated, and fails us, is when we have
distributions that are not symmetric, like the urn above. If there is a very
small probability of finding a red ball in an urn dominated by black ones,
then our knowledge about the absence of red balls will increase very
slowly - more slowly than at the expected square root of n rate. On the
other hand our knowledge of the presence of red balls will dramatically
improve once one of them is found. This asymmetry in knowledge is not
trivial; it is central in this book - it is a central philosophical problem for
such people as Hume and Karl Popper (on that, later).

To assess an investor’s performance, we either need more astute, and
less intuitive, techniques, or we may have to limit our assessments to
situations where our judgment is independent of the frequency of these
events.

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A MISCHIEVOUS CHILD REPLACES THE BLACK BALLS

But there is even worse news. In some cases, if the incidence of red balls
is itself randomly distributed, we will never get to know the composition
of the urn. This is called the problem of stationarity. Think of an urn
that is hollow at the bottom. As I am sampling from it, and without my
being aware of it, some mischievous child is adding balls of one color or
another. My inference thus becomes insignificant. I may infer that the
red balls represent 50% of the urn while the mischievous child, hearing
me, would swiftly replace all the red balls with black ones. This makes
much of our knowledge derived through statistics quite shaky.

The very same effect takes place in the market. We take past history
as a single homogeneous sample and believe that we have considerably
increased our knowledge of the future from the observation of the
sample of the past. What if vicious children were changing the
composition of the urn? In other words, what if things have changed?

I have studied and practiced econometrics for more than half my life
(since I was 19), both in the classroom and in the activity of a
quantitative derivatives trader. The “science” of econometrics consists
of the application of statistics to samples taken at different periods of
time, which we called time series. It is based on studying the time series
of economic variables, data, and other matters. In the beginning, when I
knew close to nothing (that is even less than today), I wondered whether
the time series reflecting the activity of people now dead or retired
should matter for predicting the future. Econometricians who knew a
lot more than I did about these matters asked no such question; this
hinted that it was in all likelihood a stupid inquiry. One prominent
econometrician, Hashem Pesaran, answered a similar question by
recommending to do “more and better econometrics”. I am now
convinced that, perhaps, most of econometrics could be useless - much
of what financial statisticians know would not be worth knowing. For a
sum of zeros, even repeated a billion times, remains zero; likewise an
accumulation of research and gains in complexity will lead to naught if
there is no firm ground beneath it. Studying the European markets of the
1990s will certainly be of great help to a historian; but what kind of
inference can we make now that the structure of the institutions and the
markets has changed so much?

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Note that the economist Robert Lucas dealt a blow to econometrics
by arguing that if people were rational then their rationality would
cause them to figure out predictable patterns from the past and adapt, so
that past information would be completely useless for predicting the
future (the argument, phrased in a very mathematical form, earned him
a Nobel Memorial Prize in Economics). We are human and act
according to our knowledge, which integrates past data. I can translate
his point with the following analogy. If rational traders detect a pattern
of stocks rising on Mondays, then, immediately such a pattern becomes
detectable, it would be ironed out by people buying on Friday in
anticipation of such an effect. There is no point searching for patterns
that are available to everyone with a brokerage account; once detected,
they would be ironed out.

Somehow, what came to be known as the Lucas critique was not
carried through by the “scientists”. It was confidently believed that the
scientific successes of the industrial revolution could be carried through
into the social sciences, particularly with such movements as Marxism.
Pseudoscience came with a collection of idealistic nerds who tried to
create a tailor-made society, the epitome of which is the central planner.
Economics was the most likely candidate for such use of science; you
can disguise charlatanism under the weight of equations, and nobody
can catch you since there is no such thing as a controlled experiment.
Now the spirit of such methods, called scientism by its detractors (like
myself), continued past Marxism, into the discipline of finance as a few
technicians thought that their mathematical knowledge could lead them
to understand markets. The practice of “financial engineering” came
along with massive doses of pseudoscience. Practitioners of these
methods measure risks, using the tool of past history as an indication of
the future. We will just say at this point that the mere possibility of the
distributions not being stationary makes the entire concept seem like a
costly (perhaps very costly) mistake. This leads us to a more
fundamental question: the problem of induction, to which we will turn
in the next chapter.

On the chromodynamics of swans. Taking Solon’s warning into
some philosophical territory. How Victor Niederhoffer taught
me empiricism ; I added deduction. Why it is not scientific to
take science seriously. Soros promotes Popper. That bookstore
on 21st and Fifth Avenue. Pascal’s wager.

From Bacon to Hume

N ow we discuss this problem viewed from the broader standpoint
of the philosophy of scientific knowledge. There is a problem in
inference well known as the problem of induction. It is a problem that
has been haunting science for a long time, but science has not been as
harmed by it as the financial markets. Why? Because the randomness
content compounds its effects. Nowhere is the problem of induction
more relevant than in my world of finance - and nowhere has it been as
ignored!

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CYGNUS ATRATUS

In his Treatise on Human Nature, the Scots philosopher David Hume
posed the issue in the following way (as rephrased in the now famous
black swan problem by John Stuart Mill): No amount of observations of
white swans can allow the inference that all swans are white, but the
observation of a single black swan is sufficient to refute that conclusion.

Hume had been irked by the fact that science in his day (the
eighteenth century) had experienced a swing from scholasticism, entirely
based on deductive reasoning (no emphasis on the observation of the
real world) to, owing to Francis Bacon, an overreaction into naive and
unstructured empiricism. Bacon had argued against “spinning the
cobweb of learning” with little practical result. Science had shifted,
thanks to Bacon, into an emphasis on empirical observation. The
problem is that, without a proper method, empirical observations can
lead you astray. Hume came to warn us against such knowledge, and to
stress the need for some rigor in the gathering and interpretation of
knowledge - what is called epistemology (from episteme, Greek for
learning). Hume is the first modern epistemologist, (epistemologists are
often called methodologists or philosophers of science). What I am
writing here is not strictly true, for Hume said things far worse than
that; he was an obsessive skeptic and never believed that a link between
two items could be truly established as being causal. But we will tone
him down a bit for this book.

NIEDERHOFFER, VICTORIAN GENTLEMAN

It is worth noting that finance has its Francis Bacon in the person of
Victor Niederhoffer. He was the very first to stand against the cobweb
of learning of the University of Chicago and the efficient market religion
of the 1960s, when it was at its worst. In contrast with the scholasticism
of financial theorists, he looked at data in search of anomalies - and
found enough of them to be able to conduct a successful career in
randomness and deliver an insightful book, The Education of a
Speculator. Since then, an entire industry of such operators, called
“statistical arbitrageurs”, flourished, the major and most successful ones

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were initially his trainees. While Niederhoffer had a publicized hiccup,
some of his trainees fared well because they added rigor and method-
ology to their statistical inference. In other words, Niederhoffer’s
empiricism missed just a modicum of methodology.

I have to admit that for all my intellectual disagreements with him I
have been inspired by his empiricism and owe him a large share of my
intellectual growth. I experienced a jump in my trading style in 1996,
when Victor blurted to me that any “testable” statement should be
tested (it was so obvious but I had not done it until then). His advice
went straight home. A testable statement is one that can be broken
down into quantitative components and subjected to statistical
examination. For instance, a conventional-wisdom style statement like

accidents happen closer to home

can be tested by taking the average distance between the accident and
the domicile of the driver (if, say, about 20% of accidents happen within
a 12-mile radius). However, one needs to be careful in the inter-
pretation; a naive interpreter of the result would tell you that you are
more likely to have an accident if you drive in your neighborhood than
if you did so in remote places, which is an example of naive empiricism.
Why? Because accidents may happen closer to home simply because
people spend their time driving close to home (if people spend 20% of
their time driving in a 12-mile radius).

Since that very same day I have not made a single testable proposition
without testing it, thanks to the computer which I rarely use for non-
computational tasks. However, the differences between Victor
Niederhoffer and myself remain immense; I can use data to disprove a
proposition, never to prove one. I can use history to refute a conjecture,
never to affirm it. For instance, the statement

The market never goes down 20% in a given 3-month period

can be tested, but is completely meaningless if verified. I can quantita-
tively reject the proposition by finding counterexamples, but it is
impossible for me to accept it simply because in past data the market
never went down 20% in any 3-month period.

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Returning to the black swan problem, consider the following
statement:

Statement A: No swan is black because I looked at 4000 swans and
found none.

Statement B: Not all swans are white.

I cannot logically make statement A, no matter how many successive
white swans I may have observed in my life and may observe in the
future (except of course if I am given the privilege of observing with
certainty all available swans). It is however possible to make Statement
B merely by finding one single black swan in my sample. Indeed,
statement A was disproved by the discovery of Australia, as it led to the
sighting of the cygnus atratus, a swan variety that was jet black! The
reader will see a hint of Popper (after we are done with my semi-mentor
Victor); there is a strong asymmetry between the two statements. Such
asymmetry lies in the foundations of knowledge. It is also at the core of
my dealing with randomness as a trader.

The following inductive statement illustrates the problem of
interpreting past data without logical method:

I have just completed a thorough statistical examination of the life of
President Bush. For 55 years, close to 16,000 observations, he did not
die once. I can hence pronounce him as immortal, with a high degree
of statistical significance.

Although Victor and I trade in such an opposite manner that many of
his trades end up in my inventory, I have a large measure of respect for
him. He sells out-of-the-money options for a living; I buy them for a living
(by selling an out-of-the-money option one is betting that an event will
not happen; by buying one I am merely betting that it may happen). He
tries to make steady income, I prefer a lumpy and rare payoff. Although
we seem to be diametrically opposite traders, we share many superficial
personal traits. These may be worth bringing in here because we both
make our private traits part of our trading and make a thin distinction
between activities middlebrow people call “work” and those they call
“leisure”. Both of us are traders trying to live under the illusion of

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operating a scientific laboratory. Both of us surround ourselves with
scholars and scientists, not businessmen (talking to successful scientists is
a good discipline to avoid pedestrianism in our own thinking). Both of us
try to lead the lives of the Victorian gentleman scholar with books
scattered around us, by escaping many of the popular accretions of the
twentieth century. Both of us glorify our personal idiosyncrasies to avoid
bearing any intellectual resemblance to the crowd. Both of us obsessively
pursue athletic activities on a daily basis (but he is competitive and
competition in sports repels me). Victor’s model seems to be the Victorian
gentleman (like his hero Francis Galton, the tinkering cousin of Charles
Darwin, who is the true inspiration of all applied statisticians) while, like
a true Victorian, I am first and last a classicist and remain steeped in the
Greco-Roman culture in which I grew up (my heroes are rather literary
figures). Both of us avoid the media, television, newspapers, although
Victor is far more vigorous than I in such strictures. Both of us avoid
chitchat and small talk like the plague (too much left-column noise).

Sir Karl’s Promoting Agent

Next I will discuss how I discovered Karl Popper via another trader,
perhaps the only one I have ever truly respected. I do not know if it
applies to other people, but, in spite of my being a voracious reader, I
have rarely been truly affected in my behavior (in any durable manner)
by anything I have read. A book can make a strong impression, but such
an impression tends to wane after some newer impression replaces it in
my brain (a new book). I have to discover things by myself (recall The
Stove is Hot section in Chapter 2). These self discoveries last.

One exception of ideas that stuck with me are those of Sir Karl, whom
I discovered (or perhaps rediscovered) through the writings of the trader
and self-styled philosopher George Soros who seemed to have organized
his life by becoming a promoter of the ideas of Karl Popper. What I
learned from George Soros was not quite in the way he perhaps intended
us to learn from him. I disagreed with his statements when it came to
economics and philosophy - but somehow I succumbed to the charm of

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this Hungarian man who like me is ashamed of being a trader and prefers
his trading to be a minor extension of his intellectual life (it can be seen in
his first book The Alchemy of Finance). Having never been impressed by
people with money (and I have met plenty of those throughout my life), I
did not look at any of them as remotely a role model for me. Perhaps the
opposite effect holds, as I am generally repelled by the wealthy, generally
because of the attitude of epic heroism that usually accompanies rapid
enrichment. Soros was the only one who seemed to share my values. He
wanted to be taken seriously as a Middle European professor who
happened to have gotten rich owing to the validity of his ideas (it was
only by failing to gain acceptance by other intellectuals that he would try
to gain alpha status through his money, sort of like a seducer who after
trying hard, would end up using such an appendage as the red Ferrari to
seduce the girl). In addition, although Soros did not come across very
clearly in his writings, he knew how to handle randomness, by keeping a
critical open mind and changing his opinions with minimal shame (which
carries the side effect of making him treat people like napkins). He
walked around calling himself fallible, but was so potent because he
knew it while others had loftier ideas about themselves. He understood
Popper. He lived a Popperian life.

As an aside, Popper was not new to me. I had briefly heard of Karl
Popper when I was in my teens and early twenties, as part of a
motivated education in Europe and the United States. But I did not
understand his ideas as presented then, nor did I think it would be
important (like metaphysics) for anything in life. I was at the age when
one felt like one needed to read everything, which prevented one from
making contemplative stops. Such hurry made it hard to detect that
there was something important in Popper. It was either my conditioning
by the intellectual-chic culture at the time (too much Plato, too many
Marxists, too much Hegel, too many pseudoscientific intellectuals), the
educational system (too many conjectures propounded as truth) or the
fact that I was too young and was reading too much then to make a
bridge to reality.

Popper then slipped out of my mind without hanging on a single brain
cell - there was nothing in the baggage of a boy without experience to let it
stick. Besides, having started trading, I entered an anti-intellectual phase; I
needed to make a non-random buck to secure my newly lost future and

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wealth that had just evaporated with the Lebanese war (until then I was
living with the desire to become a comfortable man of leisure like almost
everyone in my family, over the past two centuries). I suddenly felt
financially insecure and feared becoming an employee of some firm that
would turn me into a corporate slave with “work ethics” (whenever I hear
work ethics I interpret inefficient mediocrity ). I needed the backing of my
bank account so I could buy time to think and enjoy life. The last thing I
needed was immediate philosophizing and work at the local McDonald’s.
Philosophy, to me, became something rhetorical people did when they had
plenty of time on their hands; it was an activity reserved to those who are
not well versed in quantitative methods and other productive things. It
was a pastime that should be limited to late hours, in bars around the
campuses, when one had a few drinks and a light schedule - provided one
forgot the garrulous episode as early as the next day. Too much of it can
get a man in trouble, perhaps turn one into a Marxist ideologue. Popper
was not to reemerge until I secured my career as a trader.

LOCATION, LOCATION

It is said that people generally remember the time and geographic
condition where they were swept with a governing idea. The religious
poet and diplomat Paul Claudel remembers the exact spot of his
conversion (or re-conversion) to Catholicism in the Cathedral Notre-
Dame of Paris, near a precise column. Thus I remember exactly the spot
at Barnes and Noble on 21st Street and Fifth Avenue where in 1987,
inspired by Soros, I read 50 pages of The Logic of Scientific Discovery
and feverishly bought all the Popper titles I could get my hands on lest
they run out of stock. It was in a sparsely lit side-room that had a
distinctive smell of mildew. I remember vividly the thoughts that rushed
through my head like a revelation.

Popper turned out to be exactly the opposite of what I initially
thought about “philosophers”; he was the epitome of no nonsense. By
then I had been an option trader for a couple of years and I felt angry
that I was being taken for a total ride by the academic researchers in
finance, particularly since I was deriving my income from the failure of
their models. I had already started talking to finance academics as part

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of my involvement with derivatives and I had trouble getting through to
them some basic points about financial markets (they believed in their
models a little too much). There was all along lurking in any mind the
idea that these researchers had missed a point, but I did not quite know
what it was. It was not what they knew, it was how they knew it that
was the subject of my annoyance.

popper’s answer

Popper came up with a major answer to the problem of induction (to me
he came up with the answer). No man has influenced the way scientists
do science more than Sir Karl - in spite of the fact that many of his
fellow professional philosophers find him quite naive (to his credit, in
my opinion). Popper’s idea is that science is not to be taken as seriously
as it sounds (Popper when meeting Einstein did not take him as the
demigod he thought he was). There are only two types of theories:

1. Theories that are known to be wrong, as they were tested and
adequately rejected (he calls them falsified).

2. Theories that have not yet been known to be wrong, not falsified yet,
but are exposed to be proved wrong.

Why is a theory never right} Because we will never know if all the
swans are white (Popper borrowed the Kantian idea of the flaws in our
mechanisms of perception). The testing mechanism may be faulty.
However, the, statement that there is a black swan is possible to make. A
theory cannot be verified. To paraphrase baseball coach Yogi Berra
again, past data has a lot of good in it, but it is the bad side that is bad. It
can only be provisionally accepted. A theory that falls outside of these
two categories is not a theory. A theory that does not present a set of
conditions under which it would be considered wrong would be termed
charlatanism - they would be impossible to reject otherwise. Why?.
Because the astrologist can always find a reason to fit the past event, by
saying that Mars was probably in line but not too much so (likewise to
me a trader who does not have a point that would make him change his
mind is not a trader). Indeed the difference between Newtonian physics,
which was falsified by Einstein’s relativity, and astrology lies in the

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following irony. Newtonian physics is scientific because it allowed us to
falsify it, as we know that it is wrong, while astrology is not because it
does not offer conditions under which we could reject it. Astrology
cannot be disproved, owing to the auxiliary hypotheses that come into
play. Such point lies at the basis of the demarcation between science and
nonsense (called “the problem of demarcation”).

More practically to me, Popper had many problems with statistics
and statisticians. He refused to blindly accept the notion that knowledge
can always increase with incremental information - which is the
foundation of statistical inference. It may in some instances, but we do
not know which ones. Many insightful people, such as John Maynard
Keynes, independently reached the same conclusions. Sir Karl’s
detractors believe that favorably repeating the same experiment again
and again should lead to an increased comfort with the notion that “it
works”. I came to understand Popper’s position better once I saw the
first rare event ravaging a trading room. Sir Karl feared that some type
of knowledge did not increase with information - but which type we
could not ascertain. The reason I feel that he is important for us traders
is because to him the matter of knowledge and discovery is not so much
in dealing with what we know, as in dealing with what we do not know.
His famous quote:

These are men with bold ideas, but highly critical of their own ideas ;
they try to find whether their ideas are right by trying first to find
whether they are not perhaps wrong. They work with bold
conjectures and severe attempts at refuting their own conjectures.

“These” are scientists. But they could be anything.

Putting the master in context, Popper was rebelling against the growth
of science. Popper intellectually came to the world with the dramatic
shifts in philosophy as attempts were made to shift it from the verbal and
rhetorical to the scientific and rigorous, as we saw with the presentation
of the Vienna Circle in Chapter 4. These people were sometimes called
the logical positivists, after the movement called positivism pioneered in
France in the nineteenth century by Auguste Comte, where positivism
meant scientification of things (literally everything under the sun). It was
the equivalent of bringing the industrial revolution into the soft sciences.

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Without dwelling on positivism, I have to note that Popper is the antidote
to positivism. To him, verification is not possible. Verificationism is
more dangerous than anything else. Taken to the extreme, Popper’s ideas
appear naive and primitive - but they work. Note that his detractors call
him a naive falsificationist.

I am an exceedingly naive falsificationist. Why? Because I can survive
being one. My extreme and obsessive Popperism is carried out as
follows. I speculate in all of my activities on theories that represent some
vision of the world, but with the following stipulation: no rare event
should harm me. In fact, I would like all conceivable rare events to help
me. My idea of science diverges with that of the people around me
walking around calling themselves scientists. Science is mere
speculation, mere formulation of conjecture.

OPEN SOCIETY

Popper’s falsificationism is intimately connected to the notion of an
open society. An open society is one in which no permanent truth is held
to exist; this would allow counterideas to emerge. Karl Popper shared
ideas with his friend, the low-key economist Von Hayek who endorsed
capitalism as a state in which prices can disseminate information that
bureaucratic socialism would choke. Both notions of falsificationism
and open society are, counterintuitively, connected to those of a
rigorous method for handling randomness in my day job as a trader.
Clearly, an open mind is a necessity when dealing with randomness.
Popper believed* that any idea of Utopia is necessarily closed in the fact
that it chokes its own refutations. The simple notion of a good model for
society that cannot be left open for falsification is totalitarian. I learned
from Popper, in addition to the difference between an open and a closed
society, that between an open and a closed mind.

NOBODY IS PERFECT

I have some sobering information about Popper the man. Witnesses of
his private life find him rather un-Popperian. The philosopher and

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109

Oxford don Brian Magee 6 who befriended him for close to three
decades depicts him as unworldly (except in his youth) and narrowly
focused on his work. He spent the last 50 years of his long career
(Popper lived 92 years) closed to the outside world, insulated from
outside distractions and stimulation. Popper also engaged in giving
people “firm sounding advice about their career or their private life,
though he had little understanding of either. All this, of course, was in
direct contravention of his professed (and indeed genuine) beliefs, and
practices, in philosophy.”

He was not much better in his youth. Members of the Vienna Circle
tried to avoid him, not because of his divergent ideas, but because he
was a social problem. “He was brilliant, but self-focused, both insecure
and arrogant, irascible and self-righteous. He was a terrible listener and
bent on winning arguments at all costs. He had no understanding of
group dynamics and no ability to negotiate them”. 7

I will refrain from commonplace discourse about the divorce between
those who have ideas and those who carry them in practice, except to
bring out the interesting genetics problem; we like to emit logical and
rational ideas but we do not necessarily enjoy this execution. Strange as
it sounds, this point has only been discovered very recently (we will see
that we are not genetically fit to be rational and act rationally; we are
merely fit for the maximum probability of transmitting our genes in
some given unsophisticated environment). Also strange as it sounds,
George Soros, obsessively self-critical, seems to be more Popperian than
Popper in his professional behavior.

pascal’s wager

I conclude with the exposition of my own method of dealing with the
problem of induction. The philosopher Pascal proclaimed that the
optimal strategy for humans is to believe in the existence of God. For
if God exists, then the believer would be rewarded. If he does not
exist, the believer would have nothing to lose. Accordingly, we need to
accept the asymmetry in knowledge; there are situations in which
using statistics and econometrics can be useful. But I do not want my
life to depend on it.

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Like Pascal, I will therefore state the following argument. If the
science of statistics can benefit me in anything, I will use it. If it poses a
threat, then I will not. I want to take the best of what the jiast can give
me without its dangers. Accordingly, I will use statistics and inductive
methods to make aggressive bets, but I will not use them to manage my
risks and exposure. Surprisingly, all the surviving traders I know seem to
have done the same. They trade on ideas based on some observation
(that includes past history) but, like the Popperian scientists, they make
sure that the costs of being wrong are limited (and their probability is
not derived from past data). Unlike Carlos and John, they know before
getting involved in the trading strategy which events would prove their
conjecture wrong and allow for it (recall that Carlos and John used past
history both to make their bets and measure their risk). They would then
terminate their trade. This is called a stop loss, a predetermined exit
point, a protection from the black swan. I find it rarely practiced.

Thank You Solon

Finally, I have to confess that upon finishing my writing of Part I that
writing about the genius of Solon’s insight has carried an extreme effect
on both my thinking and my private life. The composition of Part I
made me even more confident in my withdrawal from the media and my
distancing myself from other members of the business community,
mostly other investors and traders for whom I am developing more and
more contempt. I am currently enjoying a thrill of the classics I have not
felt since childhood. My mind, by escaping the news pollution, allowed
me to evade the bull market that prevailed over the past 15 years (and
professionally benefit from its demise). I am now thinking of the next
step: to recreate a low-information, more deterministic ancient time, say
in the nineteenth century, all the while benefiting from some of the
technical gains (such as the Monte Carlo engine), all of the medical
breakthroughs and all the gains of social justice of our age. I would then
have the best of everything. This is called evolution.

I f one puts an infinite number of monkeys in front of (strongly built)
typewriters, and lets them clap away, there is a certainty that one of
them would come out with an exact version of the Iliad. Upon
examination, this may be less interesting a concept than it appears at
first: such probability is very low. But let us carry the reasoning one step
beyond. Now that we have found that hero among monkeys, would any
reader invest his life’s savings on a bet that the monkey would write the
Odyssey next?

In this story, it is the second step that is interesting. How much can
past performance (here the typing of the Iliad) be relevant in forecasting
future performance? The same applies to any decision based on past
performance, merely relying on the attributes of the past time series.
Think about the monkey showing up at your door with his impressive
past performance. Hey, he wrote the Iliad. Quickly, sign him up for the
sequel.

The major problem with inference in general is that those whose
profession is to derive conclusions from data often fall into the trap
faster and more confidently than others. The more data we have, the
more likely we are to drown in it. For common wisdom among people
with a budding knowledge of probability laws is to base their decision-
making on the following principle: it is very unlikely for someone to

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perform considerably well in a consistent fashion without his doing
something right. Track records therefore become preeminent. They call
on the rule of the likelihood of such a successful run and tell themselves
that if someone performed better than the rest in the past then there is a
great chance of him performing better than the crowd in the future -
and a very great one at that. But, as usual, beware the middlebrow: a
small knowledge of probability can lead to worse results than no
knowledge at all.

IT DEPENDS ON THE NUMBER OF MONKEYS

I do not deny that if someone performed better than the crowd in the
past, there is a presumption of his ability to do better in the future. But
the presumption might be weak, very weak, to the point of being useless
in decision making. Why? Because it all depends on two factors: the
randomness content of his profession and the number of monkeys in
operation.

The initial sample size matters greatly. If there are five monkeys in the
game, I would be rather impressed with the Iliad writer, to the point of
suspecting him to be a reincarnation of the ancient poet. If there are a
billion to the power one billion monkeys I would be less impressed - as a
matter of fact I would be surprised if one of them did not get some well
known (but unspecified) piece of work, just by luck (perhaps
Casanova’s Memoirs of My Life). One monkey would even be expected
to provide us with former Vice President A1 Gore’s Earth in the Balance,
perhaps stripped of the platitudes.

This problem enters the business world more viciously than other
walks of life, owing to the high dependence on randomness (we have
already belabored the contrast between randomness-dependent business
with dentistry). The greater the number of businessmen, the greater the
likelihood of one of them performing in a stellar manner just by luck. I.
have rarely seen anyone count the monkeys. In the same vein, few count
the investors in the market in order to calculate, instead of the
probability of success, the conditional probability of successful runs
given the number of investors in operation over a given market history.

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VICIOUS REAL LIFE

There are other aspects to the monkeys problem; in real life the other
monkeys are not countable, let alone visible. They are hidden away, as
one sees only the winners - it is natural for those who failed to vanish
completely. Accordingly, one sees the survivors, and only the survivors,
which imparts such a mistaken perception of the odds. We do not
respond to probability, but to society’s assessment of it. As we saw with
Nero Tulip, even people with training in probability respond
unintelligently to social pressure.

THIS SECTION

Part I described situations where people do not understand the rare
event, and do not seem to accept either the possibility of its occurrence
or the dire consequences of such occurrence. It also set out my own
ideas, those that do not seem to have been explored in the literature. But
a book on randomness is not complete without a presentation of what
possible biases one might have aside from the deformations caused by
the rare event. The business of Part II is more pedestrian; I will rapidly
provide a synthesis of the biases of randomness as discussed in the now
abundant literature on the subject.

These biases can be outlined as follows: (a) the survivorship biases
(a.k.a. monkeys on a typewriter), arising from the fact that we see only
winners and get a distorted view of the odds (Chapters 8 and 9, Too
Many Millionaires and Fry an Egg), (b) the fact that luck is most
frequently the reason for extreme success (Chapter 10, Loser Takes All),
and (c) the biological handicap of our inability to understand
probability (Chapter 11, Randomness and Our Brain).

Three illustrations of the survivorship bias. Why very few
people should live on Park Avenue. The millionaire next door
has very flimsy clothes. An overcrowding of experts.

How To Stop the Sting of Failure

SOMEWHAT HAPPY

M arc lives on Park Avenue in New York City with his wife Janet
and their three children. He makes $500,000 a year, give or take
a boom or a recession - he does not believe that the recent spurt in
prosperity is here to last and has not mentally adjusted yet to his recent
abrupt rise in income. A rotund man in his late forties, with spongy
features that make him look ten years older than his age, he leads the
seemingly comfortable (but heckled) life of a New York city lawyer. But
he is on the quiet side of Manhattan residents. Marc is clearly not the
man one would expect to go bar-hopping or attend late night Tribecca
and Soho parties. He and his wife have a country house and a rose
garden and tend to be concerned, like many people of their age,

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mentality, and condition, with (in the following order) material
comfort, health, and status. Weekdays, he does not come home until
at least 9.30 p.m. and, at times, he can be found in the office at close to
midnight. By the end of the week, Marc is so fatigued that he falls asleep
during their three-hour drive to “the house”; and Marc spends most of
Saturday lying in bed recovering and healing.

Marc grew up in a small town in the midwest, the son of a quiet tax
accountant who worked with sharp yellow pencils. His obsession with
sharpness was so strong that he carried a sharpener in his pocket at all
times. Marc exhibited very early signs of intelligence. He did extremely
well in high school. He attended Harvard College, then Yale Law
School. Not bad, one would say. Later his career took him to corporate
law, where he started working on large cases for a prestigious New
York law firm, with barely enough hours left for him to brush his teeth.
This is not too much an exaggeration, for he ate almost all of his
dinners in the office, accumulating body fat and Brownie points
towards his partnership. He later became a partner within the usual
seven years, but not without the usual human costs. His first wife
(whom he met in college) left him, as she was tired of an absentee
lawyer husband and weary of the deterioration in his conversation -
but, ironically, she ended up moving in with and later marrying another
New York lawyer, probably with a no-less flat conversation, but who
made her happier.

j TOO MUCH WORK

Marc’s body became progressively flabbier, and his tailored suits needed
periodic visits to the tailor, in spite of his occasional crash diets. After he
got over the depression of the abandonment, he started dating Janet, his
paralegal, and promptly married her. They had three children in quick
succession, bought the Park Avenue apartment, and the country house.

Janet’s immediate acquaintance is composed of the other parents of
the Manhattan private school attended by their children, and their
neighbors at the co-operative apartment building where they live. From
a materialistic standpoint, they come at the low end of such a set,
perhaps even at the exact bottom. They would be the poorest of these

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circles, as their co-op is inhabited by extremely successful corporate
executives, Wall Street traders, and high-flying entrepreneurs. Their
children’s private school harbors the second set of children of corporate
raiders, from their trophy wives - perhaps even the third set, if one takes
into account the age discrepancy and the model-like features of the other
mothers. By comparison, Marc’s wife Janet, like him, presents a homely
country-home-with-a-rose-garden type of appearance.

you’re a failure

Marc’s strategy of staying in Manhattan may be rational, as his
demanding work hours would make it impossible for him to commute.
But the costs on his wife Janet are monstrous. Why? Because of their
relative nonsuccess - as geographically defined by their Park Avenue
neighborhood. Every month or so, Janet has a crisis, giving in to the
strains and humiliations of being snubbed by some other mother at the
school where she picks up the children, or another woman with larger
diamonds by the elevator of the co-op where they live in the smallest type
of apartments (the G line). Why isn’t her husband so successful? Isn’t he
smart and hard working? Didn’t he get close to 1600 at the SAT? Why is
this Ronald Something whose wife never even nods to Janet, worth
hundred of millions when her husband went to Harvard and Yale and
has such a high I.Q., and has hardly any substantial savings?

We will not get too involved in the Chekovian dilemmas in the
private lives of Marc and Janet, but their case provides a very common
illustration of the emotional effect of survivorship bias. Janet feels that
her husband is a failure, by comparison, but she is mis-computing the
probabilities in a gross manner - she is using the wrong distribution to
derive a rank. As compared to the general U.S. population, Marc has
done very well, better than 99.5% of his compatriots. As compared to
his high-school friends, he did extremely well, a fact that he could have
verified had he had time to attend the periodic reunions, and he would
come at the top. As compared to the other people at Harvard, he did
better than 90% of them (financially, of course). As compared to his law
school comrades at Yale, he did better than 60% of them. But as
compared to his co-op neighbors, he is at the bottom! Why? Because he

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chose to live among the people who have been successful, in an area that
excludes failure. In other words, those who have failed do not show up
in the sample at all, thus making him look as if he were not doing well at
all. By living on Park Avenue, one does not have exposure to the losers,
one only sees the winners. As we are cut to live in very small com-
munities, it is difficult to assess our situation outside of the narrowly
defined geographic confines of our habitat. In the case of Marc and
Janet, this leads to considerable emotional distress; here we have a
woman who married an extremely successful man but all she can see is
comparative failure, for she cannot emotionally compare him to a
sample that would do him justice.

Someone would rationally say to Janet: “go read this book, Fooled by
Randomness by one mathematical trader on the deformations of chance
in life; it would give you a statistical sense of perspective and would
accordingly make you feel better”. As an author, I would like to offer a
panacea for $27.95, but I would rather say that in my best hopes it may
provide an hour or so of solace. Janet may need something more drastic
for relief. I have repeated that becoming more rational, or not feeling
emotions of social slights is not part of the human race, at least not with
our current DNA code. There is no solace to be found from reasoning -
as a trader I have learned something about these unfruitful efforts to
reason against the grain. I would advise Janet to move out, and go live in
some blue-collar neighborhood where they would feel less humiliated by
their neighbors and rise in the pecking order beyond their probability of
success. They could use the deformation in the opposite direction. If
Janet cares about status, then I would even recommend some of these
large housing blocks.

Double Survivorship Biases

MORE EXPERTS

I recently read a bestseller called The Millionaire Next Door, an
extremely misleading (but almost enjoyable) book by two “experts”, in

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which the authors try to infer some attributes that are common to rich
people. They examined a collection of currently wealthy people and
found out that these are unlikely to lead lavish lives. They call such
people the accumulators; persons ready to postpone consumption in
order to amass funds. Most of the appeal of the book comes from the
simple but counterintuitive fact that these are less likely to look like very
rich people - it clearly costs money to look and behave rich, not to count
the time demands of spending money. Leading prosperous lives is time
consuming; shopping for trendy clothes, becoming conversant in
Bordeaux wines, getting to know the expensive restaurants. All these
activities can put high demands on one’s time and divert the subject
from what should be the real preoccupation, namely the accumulation
of nominal (and paper) wealth. The moral of the book is that the
wealthiest are to be found among those less suspected to be wealthy. On
the other hand, those who act and look wealthy subject their net worth
to such a drain that they inflict considerable and irreversible damage to
their brokerage account.

I will set aside the point that I see no special heroism in accumulating
money, particularly if, in addition, the person is foolish enough to not
even try to derive any tangible benefit from the wealth (aside from the
pleasure of regularly counting the beans). I have no large desire to
sacrifice much of my personal habits, intellectual pleasures, and
personal standards in order to become a billionaire like Warren Buffett,
and I certainly do not see the point of becoming one if I were to adopt
Spartan (even miserly) habits and live in my starter house. Something
about the praise lavished upon him for living in austerity while being so
rich escapes me; if austerity is the end, he should become a monk or a
social worker - we should remember that becoming rich is a purely
selfish act, not a social one. The virtue of capitalism is that society can
take advantage of people’s greed rather than their benevolence, but
there is no need to, in addition, extol such greed as a moral (or
intellectual) accomplishment (the reader can easily see that, aside from
very few exceptions like George Soros, I am not impressed by people
with money). Becoming rich is not directly a moral achievement, but
that is not where the severe flaw in the book lies.

As we said, the heroes of The Millionaire Next Door are the
accumulators, people who defer spending in order to invest. It is

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undeniable that such strategy might work; money spent bears no fruit
(except the enjoyment of the spender). But the benefits promised in the
book seem grossly overstated. A finer read of their thesis- reveals that
their sample includes a double dose of survivorship bias. In other words,
it has two compounding flaws.

VISIBILITY WINNERS

The first bias comes from the fact that the rich people selected for their
sample are among the lucky monkeys on typewriters. The authors made
no attempt to correct their statistics with the fact that they saw only the
winners. They make no mention of the “accumulators” who have
accumulated the wrong things (members of my family are experts on
that; those who accumulated managed to accumulate currencies about
to be devalued and stocks of companies that later went bust). Nowhere
do we see a mention of the fact that some people were lucky enough to
have invested in the winners; these people no doubt would make their
way into the book. There is a way to take care of the bias: lower the
wealth of your average millionaire by, say, 50%, on the grounds that the
bias causes the average net worth of the observed millionaire to be
higher by such amount (it consists in adding the effect of the losers into
the pot). It would certainly modify the conclusion.

i IT’S A BULL MARKET

As to the second, more serious flaw, I have already discussed the
problem of induction. The story focuses on an unusual episode in
history; buying its thesis implies accepting that the current returns in
asset values are permanent (the sort of belief that prevailed before the
great crash that started in 1929). Remember that asset prices have (still
at the time of writing) witnessed the greatest bull market in history and
that values did compound astronomically during the past two decades.
A dollar invested in the average stock would have grown almost twenty-
fold since 1982 - and that is the average stock. The sample might
include people who invested in stocks performing better than average.

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Virtually all of the subjects became rich from asset price inflation, in
other words from the recent inflation in financial paper and assets that
started in 1982. An investor who engaged in the same strategy during
less august days for the market would certainly have a different story to
tell. Imagine the book being written in 1982, after the prolonged erosion
of the inflation-adjusted value of the stocks, or in 1935, after the loss of
interest in the stock market.

Or consider that the United States stock market is not the only
investment vehicle. Consider the fate of those who, in place of spending
their money buying expensive toys and paying for ski trips, bought
Lebanese lira denominated Treasury bills (as my grandfather did), or
junk bonds from Michael Milken (as many of my colleagues in the
1980s did). Go back in history and imagine the accumulator buying
Russian Imperial bonds bearing the signature of Czar Nicholas II and
trying to accumulate further by cashing them from the Soviet govern-
ment, or Argentine real estate in the 1930s (as my great grandfather
did).

The mistake of ignoring the survivorship bias is chronic, even (or
perhaps especially) among professionals. How? Because we are trained
to take advantage of the information that is lying in front of our eyes,
ignoring the information that we do not see.

A brief summing up at this point: I showed how we tend to mistake
one realization among all possible random histories as the most
representative one, forgetting that there may be others. In a nutshell,
the survivorship bias implies that the highest performing realization will
be the most visible. Why? Because the losers do not show up.

A Guru's Opinion

The fund management industry is populated with gurus. Clearly, the
field is randomness-laden and the guru is going to fall into a trap,
particularly if he has no proper training in inference. At the time of
writing, there is one such guru who developed the very unfortunate
habit of writing books on the subject. Along with one of his peers, he

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computed the success of a “Robin Hood” policy of investing with the
least successful manager in a given population of managers. It consists in
switching down by taking money away from the winner and allocating
it to the loser. This goes against the prevailing wisdom of investing with
a winning manager and taking away money from a losing one. Doing so,
their “paper strategy” (i.e. as in a Monopoly™ game, not executed in
real life) derived considerably higher returns than if they stuck to the
winning manager. Their hypothetical example seemed to them to prove
that one should not stay with the best manager, as we would be inclined
to do, but rather switch to the worst manager, or at least such seems to
be the point they were attempting to convey.

Their analysis presents one severe hitch that any graduate student in
financial economics should be able to pinpoint at the first reading. Their
sample only had survivors. They simply forgot to take into account the
managers who went out of business. Such a sample includes managers
that were operating during the simulation, and are still operating today.
True, their sample included managers who did poorly, but only those
managers who did poorly and recovered, without getting out of
business. So it would be obvious that investing with those who fared
poorly at some point, but recovered (with the benefit of hindsight)
would yield a positive return! Had they continued to fare poorly, they
would be out of business and would not be included in the sample.

How should one conduct the proper simulation? By taking a
population of managers in existence, say, five years ago and running
the simulation until today. Clearly, the attributes of those who leave the
population are biased towards failure; few successful people in such a
lucrative business call it quits for making too much money. Next we
turn to a more technical presentation of these issues.

Some technical extensions of the survivorship bias. On the
distribution of “ coincidences ” in life. It is preferable to be lucky
than competent ( but you can be caught). The birthday paradox.

More charlatans (and more journalists) . How the researcher
with work ethics can find just about anything in data. On dogs

not barking.

T his afternoon I have an appointment with my dentist (it will mostly
consist in the dentist picking my brain on Brazilian bonds). I can state
with a certain level of comfort that he knows something about teeth,
particularly if I enter his office with a toothache and exit it with some form
of relief. It will be difficult for someone who knows literally nothing about
teeth to provide me with such relief, except if he is particularly lucky on
that day - or has been very lucky in his life to become a dentist while not
knowing anything about teeth. Looking at his diploma on the wall, I
determine that the odds that he repeatedly gave correct answers to the
exam questions and performed satisfactorily on a few thousand cavities
before his graduation - out of plain randomness - are remarkably small.

Later in the evening, I go to Carnegie Hall. I can say little about the
pianist; I even forgot her unfamiliar foreign sounding name. All I know

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is that she studied in some Muscovite conservatory. But I can expect to
get some music out of the piano. It will be rare to have someone who
performed brilliantly enough in the past to get to Carnegie Hall and now
turns out to have benefited from luck alone. The expectation of having a
fraud who will bang on the piano, producing only cacophonous sounds,
is indeed low enough for me to rule it out completely.

I was in London last Saturday. Saturdays in London are magical;
bustling but without the mechanical industry of a weekday or the sad
resignation of a Sunday. Without a wristwatch or a plan I found myself
in front of my favorite carvings by Canova at the Victoria and Albert
Museum. My professional bent immediately made me question whether
randomness played a large role in the carving of these marble statues.
The bodies were realistic reproductions of human figures, except that
they were more harmonious and finely balanced than anything I have
seen mother nature produce on its own (Ovid’s materiem superabat
opus comes to mind). Could such finesse be a product of luck?

I can practically make the same statement about anyone operating in
the physical world, or in a business in which the degree of randomness is
low. But there is a problem in anything related to the business world. I
am bothered because tomorrow, unfortunately, I have an appointment
with a fund manager seeking my help, and that of my friends, in finding
investors. He has what he claims is a good track record. All I can infer is
that he has learned to buy and sell. And it is harder to fry an egg than
buy and sell. Well ... the fact that he made money in the past may have
some relevance, but not terribly so. This is not to say that it is always the
case; there are some instances in which one can trust a track record, but,
alas, there are not too many of these. As the reader now knows, the fund
manager can expect to be heckled by me during the presentation,
particularly if he does not exhibit the minimum of humility and self-
doubt that I would expect from someone practicing randomness. I will
probably bombard him with questions that he may not be prepared to
answer, blinded by his past results. I will probably lecture him that.
Machiavelli ascribed to luck at least a 50% role in life (the rest was
cunning and bravura), and that was before the creation of modern
markets.

In this chapter, I discuss some well-known counterintuitive properties
of performance records and historical time series. The concept presented

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here is well known for some of its variations under the name survivorship
bias , data mining, data snooping, overfitting, regression to the mean, etc.,
basically situations where the performance is exaggerated by the
observer, owing to a misperception of the importance of randomness.
Clearly, this concept has rather unsettling implications. It extends to
more general situations where randomness may play a share, such as the
choice of a medical treatment or the interpretation of coincidental events.

When I am tempted to suggest a possible future contribution of
financial research to science in general, I adduce the analysis of data
mining and the study of survivorship biases. These have been refined in
finance but can extend to all areas of scientific investigation. Why is
finance so rich a field? Because it is one of the rare areas of investigation
where we have plenty of information (in the form of abundant price
series), but no ability to conduct experiments as in, say, physics. This
dependence on past data brings about its salient defects.

Fooled by Numbers

PLACEBO INVESTORS

I have often been faced with questions of the sort: “Who do you think
you are to tell me that I might have been plain lucky in my life?” Well,
nobody really believes that he or she was lucky. My approach is that,
with our Monte Carlo engine, we can manufacture purely random
situations. We can do the exact opposite of conventional methods; in
place of analyzing real people hunting for attributes we can create
artificial ones with precisely known attributes. Thus we can manufac-
ture situations that depend on pure, unadulterated luck, without the
shadow of skills or whatever we have called non-luck in Table P.l. In
other words, we can man-make pure nobodies to laugh at; they will be
by design stripped of any shadow of ability (exactly like a placebo drug).

We saw in Chapter 5 how people may survive owing to traits that
momentarily fit the given structure of randomness. Here we take a far
simpler situation where we know the structure of randomness-, the first

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such exercise is a finessing of the old popular saying that even a broken
clock is right twice a day. We will take it a bit further to show that
statistics is a knife that cuts on both sides. Let us use the Monte Carlo
generator introduced earlier and construct a population of 10,000
fictional investment managers (the generator is not terribly necessary
since we can use a coin, or even do plain algebra, but it is considerably
more illustrative - and fun). Assume that they each have a perfectly fair
game; each one has a 50% probability of making $10,000 at the end of
the year, and a 50% probability of losing $10,000. Let us introduce an
additional restriction; once a manager has a single bad year, he is
thrown out of the sample, good-bye and have a nice life. Thus we will
operate like the legendary speculator George Soros who was said to tell
his managers gathered in a room: “half of you guys will be out by next
year” (with an Eastern European accent). Like Soros, we have extremely
high standards; we are looking only for managers with an unblemished
record. We have no patience for low performers.

The Monte Carlo generator will toss a coin; heads and the manager
will make $10,000 over the year, tails and he will lose $10,000. We run
it for the first year. At the end of the year, we expect 5,000 managers to
be up $10,000 each, and 5,000 to be down $10,000. Now we run the
game a second year. Again, we can expect 2,500 managers to be up two
years in a row; another year, 1,250; a fourth one, 625; a fifth, 313. We
have now, simply in a fair game, 313 managers who made money for
five years in a row. Out of pure luck.

NOBODY HAS TO BE COMPETENT

Let’s push the argument further to make it more interesting. We create a
cohort that is composed exclusively of incompetent managers. We will
define an incompetent manager as someone who has a negative expected
return, the equivalent of the odds being stacked against him. We instruct,
the Monte Carlo generator now to draw from an urn. The urn has 100
balls, 45 black and 55 red. By drawing with replacement, the ratio of
red to black balls will remain the same. If we draw a black ball, the
manager will earn $10,000. If we draw a red ball, he will lose $10,000.
The manager is thus expected to earn $10,000 with 45% probability,

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and lose $10,000 with 55%. On average, the manager will lose $1,000
each round - but only on average.

At the end of the first year, we still expect to have 4,500 managers
turning a profit (45% of them), the second, 45% of that number, 2,025.
The third, 911; the fourth, 410; the fifth, 184. Let us give the surviving
managers names and dress them in business suits. True, they represent
less than 2% of the original cohort. But they will get attention. Nobody
will mention the other 98%. What can we conclude?

The first counterintuitive point is that a population entirely composed
of bad managers will produce a small amount of great track records. As
a matter of fact, assuming the manager shows up unsolicited at your
door, it will be practically impossible to figure out whether he is good or
bad. The results would not markedly change, even if the population
were composed entirely of managers who are expected in the long run to
lose money. Why? Because owing to volatility, some of them will make
money. We can see here that volatility actually helps bad investment
decisions.

The second counterintuitive point is that the expectation of the
maximum of track records, with which we are concerned, depends more
on the size of the initial sample, than on the individual odds per
manager. In other words the number of managers with great track
records in a given market depends far more on the number of people
who started in the investment business (in place of going to dental
school), rather than on their ability to produce profits. It also depends
on the volatility. Why do I use the notion of expectation of the
maximum? Because I am not concerned at all with the average track
record. I will get to see only the best of the managers, not all of the
managers. This means that we will see more “excellent managers” in
2002 than in 1998, provided the cohort of beginners was greater in
1997 than it was in 1993 - I can safely say that it was.

ERGODICITY

To get more technical, I have to say that people believe that they can
figure out the properties of the distribution from the sample they are
witnessing. When it comes to matters that depend on the maximum, it is

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altogether another distribution that is being inferred, that of the best
performers. We call the difference between the average of such
distribution and the unconditional distribution of winners and losers
the survivorship bias - here the fact that about 3% of the initial cohort
will make money five years in a row. In addition, this example illustrates
the properties of ergodicity, namely, that time will eliminate the
annoying effects of randomness. Looking forward, in spite of the fact
that these managers were profitable in the past five years, we expect
them to break even in any future time period. They will fare no better
than those of the initial cohort who failed earlier in the exercise. Ah, the
long term.

A few years ago, when I told one A., a then Master-of-the-Universe
type, that track records were less relevant than he thought, he found the
remark so offensive that he violently flung his cigarette lighter in my
direction. The episode taught me a lot. Remember that nobody accepts
randomness in his own success, only his failure. His ego was pumped up
as he was heading up a department of “great traders” who were then
temporarily making a fortune in the markets. They subsequently blew
up during the harsh New York winter of 1994 (it was the bond market
crash that followed the surprise interest rate hike by Alan Greenspan).
The interesting part is that six years later I can hardly find any of them
still trading (ergodicity).

Recall that the survivorship bias depends on the size of the initial
population. The information that a person made money in the past, just
by itself, is neither meaningful nor relevant. We need to know the size of
the population from which he came. In other words, without knowing
how many managers out there have tried and failed, we will not be able
to assess the validity of the track record. If the initial population
includes ten managers, then I would give the performer half my savings
without a blink. If the initial population is composed of 10,000
managers, I would ignore the results. The latter situation is generally the
case; these days so many people have been drawn to the financial
markets. Many college graduates are trading as a first career, failing,
then going to dental school.

If, as in a fairy tale, these fictional managers materialized into real
human beings, one of these could be the person I am meeting tomorrow
at 11.45 a.m. Why did I select 11.45 a.m.? Because I will question him

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about his trading style. I need to know how he trades. I will then be able
to claim that I have to rush to a lunch appointment if the manager puts
too much emphasis on his track record.

Life Is Coincidental

Next we look at the extensions to real life of our bias in the
understanding of the distribution of coincidences.

THE MYSTERIOUS LETTER

You get an anonymous letter on January 2nd informing you that the
market will go up during the month. It proves to be true, but you
disregard it owing to the well-known January effect (stocks have gone
up historically during January). Then you receive another one on Feb 1st
telling you that the market will go down. Again, it proves to be true.
Then you get another letter on March 1st - same story. By July you are
intrigued by the prescience of the anonymous person and you are asked
to invest in a special offshore fund. You pour all your savings into it.
Two months later, your money is gone. You go spill your tears on your
neighbor’s shoulder and he tells you that he remembers that he received
two such mysterious letters. But the mailings stopped at the second
letter. He recalls that the first one was correct in its prediction, the other
incorrect.

What happened? The trick is as follows. The con operator pulls
10,000 names out of a phone book. He mails a bullish letter to one half
of the sample, and a bearish one to the other half. The following month
he selects the names of the persons to whom he mailed the letter whose
prediction turned out to be right, that is, 5,000 names. The next month
he does the same with the remaining 2,500 names, until the list narrows
down to 500 people. Of these there will be 200 victims. An investment
in a few thousand dollars worth of postage stamps will turn into several
million.

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AN INTERRUPTED TENNIS GAME

It is not uncommon for someone watching a tennis game on television to
be bombarded by advertisements for funds that did (until that minute)
outperform others by some percentage over some period. But, again,
why would anybody advertise if he didn’t happen to outperform the
market? There is a high probability of the investment coming to you if
its success is caused entirely by randomness. This phenomenon is what
economists and insurance people call adverse selection. Judging an
investment that comes to you requires more stringent standards than
judging an investment you seek, owing to such selection bias. For
example, by going to a cohort composed of 10,000 managers, I have 2/
100 chances of finding a spurious survivor. By staying home and
answering my door bell, the chance of the soliciting party being a
spurious survivor is closer to 100%.

THE BIRTHDAY PARADOX

The most intuitive way to describe the data mining problem to a non-
statistician is through what is called the birthday paradox, though it is
not really a paradox, simply a perceptional oddity. If you meet
someone randomly, there is a one in 365.25 chance of your sharing
their birthday, and a considerably smaller one of having the exact
birthday of the same year. So, sharing the same birthday would be a
coincidental event that you would discuss at the dinner table. Now let
us look at a situation where there are 23 people in a room. What is the
chance of there being two people with the same birthday? About 50%.
For we are not specifying which people need to share a birthday; any
pair works.

it’s a small world!

A similar misconception of probabilities arises from the random
encounters one may have with relatives or friends in highly unexpected
places. “It’s a small world” is often uttered with surprise. But these are

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not improbable occurrences - the world is much larger than we think. It
is just that we are not truly testing for the odds of having an encounter
with one specific person, in a specific location at a specific time. Rather,
we are simply testing for any encounter, with any person we have ever
met in the past, and in any place we will visit during the period
concerned. The probability of the latter is considerably higher, perhaps
several thousand times the magnitude of the former.

When the statistician looks at the data to test a given relationship, say
to ferret out the correlation between the occurrence of a given event, like
a political announcement, and stock market volatility, odds are that the
results can be taken seriously. But when one throws the computer at
data, looking for just about any relationship, it is certain that a spurious
connection will emerge, such as the fate of the stock market being linked
to the length of women’s skirts. And just like the birthday coincidences,
it will amaze people.

DATA MINING, STATISTICS, AND CHARLATANISM

What is your probability of winning the New Jersey lottery twice? One
in 17 trillion. Yet it happened to Evelyn Adams, whom the reader might
guess should feel particularly chosen by destiny. Using the method we
developed above, Harvard’s Percy Diaconis and Frederick Mosteller
estimated at 30 to 1 the probability that someone, somewhere, in a
totally unspecified way, gets so lucky!

Some people carry their data mining activities into theology - after
all, ancient Mediterraneans used to read potent messages in the entrails
of birds. An interesting extension of data mining into biblical exegesis is
provided in The Bible Code by Michael Drosnin. Drosnin, a former
journalist (seemingly innocent of any training in statistics), aided by the
works of a “mathematician”, helped “predict” Rabin’s assassination by
deciphering a bible code. He informed Rabin, who obviously did not
take it too seriously. The Bible Code finds statistical irregularities in the
Bible; these help predict some such events. Needless to say that the book
sold well.

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THE BEST BOOK I HAVE EVER READ!

My favorite time is spent in bookstores, where I aimlessly move from
book to book in an attempt to make a decision as to whether to invest
the time in reading it. My buying is frequently made on impulse, based
on superficial but suggestive clues. Frequently I have nothing but a book
jacket as appendage to my decision making. Jackets often contain praise
by someone, famous or not, or excerpts from a book review. Good
praise by a famous and respected person or a well-known magazine
would sway me into buying the book.

What is the problem? I tend to confuse a book review, which is
supposed to be an assessment of the quality of the book, with the best
book reviews, marred with the same survivorship biases. I mistake the
distribution of the maximum of a variable with that of the variable
itself. The publisher will never put on the jacket of the book anything
but the best praise. Some authors go even a step beyond, taking a tepid
or even unfavorable book review and selecting words in it that appear to
praise the book. One such example came from one Paul Wilmott (an
English financial mathematician of rare brilliance and irreverence) who
managed to announce that I gave him his “first bad review”, yet used
excerpts from it as praise on the book jacket (we later became friends,
which allowed me to extract an endorsement from him).

The first time I was fooled by this bias was upon buying, when I was
16, Manhattan Transfer, a book by John Dos Passos, the American
writer, based on praise on the jacket by the philosopher Jean-Paul Sartre,
who claimed something to the effect that Dos Passos was the greatest
writer of our time. This simple remark, possibly blurted out in a state of
intoxication or extreme enthusiasm, caused Dos Passos to become
required reading in European intellectual circles, as Sartre’s remark was
mistaken for a consensus estimate of the quality of Dos Passos rather
than what it was, the best remark. (In spite of having received the Nobel
Prize in literature, Dos Passos has reverted to obscurity.)

THE BACKTESTER

A programmer helped me build a backtester. It is a software program
connected to a database of historical prices which allows me to check

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the hypothetical past performance of any trading rule of average com-
plexity. I can just apply a mechanical trading rule, like buy NASDAQ
stocks if they close more than 1.83% above their average of the previous
week, and immediately get an idea of its past performance. The screen
will flash my hypothetical track record associated with the trading rule.
If I do not like the results, I can change the percentage, to say, 1.2%. I
can also make the rule more complex. I will keep trying until I find
something that works well.

What am I doing? The exact same task of looking for the survivor
within the set of rules that can possibly work. I am fitting the rule on the
data. This activity is called data snooping. The more I try, the more I am
likely, by mere luck, to find a rule that worked on past data. A random
series will always present some detectable pattern. I am convinced that
there exists a tradable security in the Western world that would be
100% correlated with the changes in temperature in Oulan Bator,
Mongolia.

To get technical, there are even worse extensions. An outstanding
recent paper by Sullivan, Timmerman and White 8 goes further and
considers that the rules that may be in use successfully today may be the
result of a survivorship bias.

Suppose that, over time, investors have experimented with technical
trading rules drawn from a very wide universe - in principle thousands
of parameter izations of a variety of types of rules. As time progresses,
the rules that happen to perform well historically receive more
attention and are considered “serious contenders” by the investment
community, while unsuccessful trading rules are more likely to be
forgotten. ...If enough trading rules are considered over time, some
rules are bound by pure luck, even in a very large sample, to produce
superior performance even if they do not genuinely possess predictive
power over asset returns. Of course, inference based solely on the
subset of surviving trading rules may be misleading in this context
since it does not account for the full set of initial trading rules, most of
which are unlikely to have underperformed.

I have to decry some excesses in back-testing that I have closely
witnessed in my private career. There is an excellent product designed

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just for that, called Omega TradeStation™ that is currently on the
market, in use by tens of thousands of traders. It even offers its own
computer language. Beset with insomnia, the computerized day-traders
become night-testers plowing the data for some of its properties. By dint
of throwing their monkeys on typewriters, without specifying what
book they want their monkey to write, they will hit upon hypothetical
gold somewhere. Many of them blindly believe in it.

One of my colleagues, a man with prestigious degrees, grew to believe
in such a virtual world to the point of losing all sense of reality. Whether
the modicum of common sense left in him might have rapidly vanished
under the mounds of simulations, or whether he might have had none to
engage in such pursuit, I cannot tell. By closely watching him I learned
that what natural skepticism he may have had vanished under the
weight of data - for he was extremely skeptical, but in the wrong area.
Ah, Hume!

A MORE UNSETTLING EXTENSION

Historically, medicine has operated by trial and error - in other words,
statistically. We know by now that there can be entirely fortuitous
connections between symptoms and treatment, and that some
medications succeed in medical trials for mere random reasons. I cannot
claim expertise in medicine, but have been a steady reader of a segment of
the medical literature over the past half decade, long enough to be
concerned with the standards, as we will see in the next chapter. Medical
researchers are rarely statisticians; statisticians are rarely medical
researchers. Many medical researchers are not even remotely aware of
this bias. True, it may play a small role, but it is certainly present. One
recent medical study links cigarette smoking to a reduction in breast
cancer, thus conflicting with all previous studies. Logic would indicate
that the result may be suspicious, the result of mere coincidence.

THE EARNINGS SEASON: FOOLED BY THE RESULTS

Wall Street analysts, in general, are trained to find the accounting tricks
that companies use to hide their earnings. They tend to beat the companies

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at that game. But they are not trained yet to deal with randomness. When a
company shows an increase in earnings once, it draws no immediate
attention. Twice, and the name starts showing up on computer screens.
Three times, and the company will merit some buy recommendation.

Just as with the track record problem, consider a cohort of 10,000
companies that are assumed on average to barely return the risk-free
rate (i.e. Treasury bonds). They engage in all forms of volatile
businesses. At the end of the first year, we will have 5,000 “star”
companies showing an increase in profits (assuming no inflation), and
I:. 5,000 “dogs”. After three years, we will have 1,250 “stars”. The stock
| review committee at the investment house will give your broker their
| name as a “strong buy”. He will leave a voice-message that he has a hot
I recommendation that necessitates immediate action. You will be e-
|; : mailed a long list of names. You will buy one or two of them.
Meanwhile, the manager in charge of your 40 IK retirement plan will be
acquiring the entire list.

We can apply the reasoning to the selection of investment categories -
; as if they were the managers in the example above. Assume you are
I standing in 1900 with hundreds of investments to look at. There are the
■ stock markets of Argentina, Imperial Russia, the United Kingdom,
Unified Germany, and plenty of others to consider. A rational person
7 would have bought not just the emerging country of the United States,
$. but those of Russia and Argentina as well. The rest of the story is well
known; while many of the stock markets like those of the United
Kingdom and the United States fared extremely well, the investor in
!>; Imperial Russia would have no better than medium-quality wallpaper in
| his hands. The countries that fared well are not a large segment of the
| initial cohort; randomness would be expected to allow a few investment
classes to fare extremely well. I wonder if those “experts” who make
i foolish (and self-serving) statements like “markets will always go up in
any 20-year period” are aware of this problem.

CANCER CURES

When I return home from an Asian or European trip, my jet lag often
causes me to rise at a very early hour. Occasionally, though very rarely, I

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switch on the TV set searching for market information. What strikes me
in these morning explorations is the abundance of claims by the
alternative medicine vendors of the curing power of their products. These
no doubt are caused by the lower advertising rates at that time. To prove
their claim, they present the convincing testimonial of someone who was
cured thanks to their methods. For instance, I once saw a former throat
cancer patient explaining how he was saved by a combination of
vitamins for sale for the exceptionally low price of $14.95 - in all
likelihood he was sincere (although of course compensated for his
account, perhaps with a lifetime supply of such medicine). In spite of our
advances, people still believe in the existence of links between disease and
cure based on such information, and there is no scientific evidence that
can convince them more potently than a sincere and emotional
testimonial. Such testimonial does not always come from the regular
guy; statements by Nobel Prize winners (in the wrong discipline) could
easily suffice. Linus Pauling, a Nobel Prize winner in chemistry, was said
to believe in vitamin C’s medicinal properties, himself ingesting massive
daily doses. With his bully pulpit, he contributed to the common belief in
vitamin C’s curative properties. Many medical studies, unable to
replicate Pauling’s claims, fell on deaf ears as it was difficult to undo
the testimonial by a “Nobel Prize winner”, even if he was not qualified to
discuss matters related to medicine.

Many of these claims have been harmless outside of the financial
profits for these charlatans - but many cancer patients may have
replaced the more scientifically investigated therapies, in favor of these
methods and died as a result of their neglecting more orthodox cures
(again, the rtonscientific methods are gathered under what is called
“alternative medicine”, that is, unproven therapies and the medical
community has difficulties convincing the press that there is only one
medicine and that alternative medicine is not medicine). The reader
might wonder about my claims that the user of these products could be
sincere, without it meaning that he was cured by the illusory treatment.
The reason is something called “spontaneous remission”, in which a
very small minority of cancer patients, for reasons that remain entirely
speculative, wipe out cancer cells and recover “miraculously”. Some
switch causes the patient’s immune system to eradicate all cancer cells
from the body. These people would have been equally cured by drinking

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a glass of Vermont spring water or chewing on dried beef as they were
by taking these beautifully wrapped pills. Finally, these spontaneous
remissions might not be so spontaneous; they might, at the bottom, have
a cause that we are not yet sophisticated enough to detect.

The late astronomer Carl Sagan, a devoted promoter of scientific
thinking and an obsessive enemy of non-science, examined the cures
from cancer that result from a visit to Lourdes in France where people
were healed by simple contact with the holy waters, and found out the
interesting fact that, of the total cancer patients who visited the place,
the cure rate was, if anything, lower than the statistical one for
spontaneous remissions. It was lower than the average for those who did
not go to Lourdes! Should a statistician infer here that cancer patients’
odds of surviving deteriorates after a visit to Lourdes?

PROFESSOR PEARSON GOES TO MONTE CARLO (LITERALLY):

RANDOMNESS DOES NOT LOOK RANDOM!

At the beginning of the twentieth century, as we were starting to develop
techniques to deal with the notion of random outcomes, several
methods were designed to detect anomalies. Professor Karl Pearson (of
Neyman-Pearson fame, familiar to every person who sat in a statistics
101 class) devised the first test of non-randomness (it was in reality a
test of deviation from normality, which, for all intents and purposes,
was the same thing). He examined millions of runs of what was called a
Monte Carlo (the old name for a roulette wheel) during the month of
July 1902. He discovered that, with a high degree of statistical
significance (with an error of less than one to a billion), the runs were
not purely random. What! The roulette wheel was not random!
Professor Pearson was greatly surprised at the discovery. But this result
in itself tells us nothing; we know that there is no such thing as a pure
random draw, for the outcome of the draw depends on the quality of the
equipment. With enough minutiae one would be able to uncover the
non-randomness somewhere (i.e. the wheel itself may not have been
perfectly balanced or perhaps the spinning ball was not completely
spherical). Philosophers of statistics call this the reference case problem,
to explain that there is no true attainable randomness in practice, only in

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theory. Besides, a manager would question whether such non-
randomness can lead to any meaningful profitable rules. If I need to
gamble $1 on 10,000 runs and expect to make $1 for my efforts, then I
would do much better in the part-time employment of a janitorial
agency.

But the result bears another suspicious element. Of more practical
relevance here is the following severe problem about non-randomness.
Even the fathers of statistical science forgot that a random series of runs
need not exhibit a pattern to look random; as a matter of fact data that
is perfectly patternless would be extremely suspicious and appear to be
man-made. A single random run is bound to exhibit some pattern - if
one looks hard enough. Note that Professor Pearson was among the first
scholars who were interested in creating artificial random data
generators, tables one could use as inputs for various scientific and
engineering simulations (the precursors of our Monte Carlo simulator).
The problem is that they did not want these tables to exhibit any form of
regularity. Yet real randomness does not look random!

I would further illustrate the point with the study of a phenomenon
well known as cancer clusters. Consider a square with 16 random darts
hitting it with equal probability of being at any place in the square. If we
divide the square into 16 smaller squares, it is expected that each smaller
square will contain one dart on average - but only on average. There is a
very small probability of having exactly 16 darts in 16 different squares.
The average grid will have more than one dart in a few squares, and no
dart at all in many squares. It will be an exceptionally rare incident that
no (cancer) cluster would show on the grid. Now, transpose our grid
with the darts in it to overlay a map of any region. Some newspaper will
declare that one of the areas (the one with more than the average of
darts) harbors radiation that causes cancer, prompting lawyers to start
soliciting the patients.

THE DOG THAT DID NOT BARK: ON BIASES IN SCIENTIFIC KNOWLEDGE

By the same argument, science is marred by a pernicious survivorship
bias, affecting the way research gets published. In a way that is similar
to journalism, research that yields no result does not make it to print.

IT IS EASIER TO BUY AND SELL THAN FRY AN EGG

141

That may seem sensible, as newspapers do not have to have a screaming
headline saying that nothing new is taking place (though the Bible was
smart enough to declare ein chadash tacht hashemesh - “nothing new
under the sun”, providing the information that things just do recur). The
problem is that a finding of absence and an absence of findings get
mixed together. There may be great information in the fact that nothing
took place. As Sherlock Holmes noted in the Silver Blaze case - the
curious thing was that the dog did not bark. More problematically,
there are plenty of scientific results that are left out of publications
because they are not statistically significant, but nevertheless provide
information . 9

I Have No Conclusion

I am frequently asked the question: when is it truly not luck? To be
honest, I am unable to answer it. I can tell that person A seems less lucky
than person B, but the confidence in such knowledge can be so weak as
to be meaningless. I prefer to remain a skeptic. People frequently
misinterpret my opinion. I never said that every rich man is an idiot and
every unsuccessful person unlucky, only that in absence of much
additional information I prefer to reserve my judgment. It is safer.

The nonlinear viciousness of life. Moving to Bel Air and
acquiring the vices of the rich and famous. Why Microsoft’s Bill
Gates may not be the best in his business (but please do not
inform him of such a fact). Depriving donkeys of food.

N ext I put the platitude that life is unfair under some examination,
but in a new angle. The twist: life is unfair in a nonlinear way.
This chapter is about how a small advantage in life can translate into a
highly disproportionate payoff, or, more viciously, how no advantage at
all, but a very, very small help from randomness, can lead to a bonanza.

The Sandpile Effect

First we define nonlinearity. There are many ways to present it, but one
of the most popular ones in science is what is called the sandpile effect,
which I can illustrate as follows. I am currently sitting on a beach in

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ON THE NONLINEARITIES OF LIFE 143

Copacabana, in Rio de Janeiro, attempting to do nothing strenuous,
away from anything to read and write (unsuccessfully, of course, as I am
mentally writing these lines). I am playing with plastic beach toys
borrowed from a child, trying to build an edifice - modestly but doggedly
attempting to emulate the tower of Babel. I continuously add sand to the
top, slowly raising the entire structure. My Babylonian relatives thought
they could thus reach the heavens. I have more humble designs; to test
how high I could go before it would topple. I keep adding sand, testing to
see how the structure would ultimately collapse. Unused to seeing adults
build sandcastles, a child looks at me with amazement.

In time - and much to the onlooking child’s delight - my castle
inevitably topples to rejoin the rest of the sand on the beach. It could be
said that the last grain of sand is responsible for the destruction of the
entire structure. What we are witnessing here is a nonlinear effect
resulting from a linear force exerted on an object. A very small
additional input, here the grain of sand, caused a disproportionate
result, namely the destruction of my starter tower of Babel. Popular
wisdom has integrated many such phenomena, as witnessed by such
expressions as “the straw that broke the camel’s back” or “the drop that
caused the water to spill”.

These nonlinear dynamics have a bookstore name; chaos theory,
which is a misnomer because it has nothing to do with chaos. Chaos
theory concerns itself primarily with functions in which a small input can
lead to a disproportionate response. Population models, for instance, can
lead to a path of explosive growth, or extinction of a species, depending
on a very small difference in the population at a starting point in time.
Another popular scientific analogy is the weather, where it has been
shown that a simple butterfly fluttering its wings in India can cause a
hurricane in New York. But the classics have their share to offer as well:
Pascal (the same of Pascal’s wager in Chapter 7) said that if Cleopatra’s
nose had been slightly shorter, the world’s fate would have changed.
Cleopatra had comely features dominated by a thin and elongated nose
that made Julius Caesar and his successor Marc Antony fall for her (here
the intellectual snob in me cannot resist dissenting against conventional
wisdom; Plutarch claimed that it was Cleopatra’s skills in conversation,
rather than her good looks, that caused the maddening infatuation of the
shakers and movers of her day; I truly believe it).

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ENTER RANDOMNESS

Things can become more interesting when randomness enters the game.
Imagine a waiting room full of actors queuing for an audition. The
number of actors who will win is clearly small, and they are the ones
generally observed by the public as representative of the profession, as
we saw in our discussion on survivorship bias. The winners would move
into Bel Air, feel pressure to acquire some basic training in the
consumption of luxury goods and, perhaps owing to the dissolute and
unrhythmic lifestyle, flirt with substance abuse. As to the others (the
great majority), we can imagine their fate; a lifetime of serving foamed
caffe latte at the neighboring Starbucks, fighting the biological clock
between auditions.

One may argue that the actor who lands the lead role that catapulted
him into fame and expensive swimming pools has some skills others
lack, some charm, or a specific physical trait that was a perfect match
for such a career path. I beg to differ. The winner may have had some
acting skills, but so do all of the others, otherwise they would not have
been in the waiting room.

It is an interesting attribute of fame that it has its own dynamics. An
actor becomes known by some parts of the public because he is known
by other parts of the public. The dynamics of such fame follow a
rotating helix, which may have started at the audition, as the selection
could have been caused by some silly detail that fitted the mood of the
examiner on that day. Had the examiner not fallen in love the previous
day with a person of similar sounding last name, then our selected actor
from that particular sample history would be serving caffe latte in the
intervening sample history.

LEARNING TO TYPE

Researchers frequently use the example of QWERTY to describe the
vicious dynamics of winning and losing in an economy, and to illustrate
how the final outcome is more than frequently the undeserved one. The
arrangement of the letters on a typewriter is an example of the success of
the least deserving method. For our typewriters have the orders of the

LOSER TAKES ALL - ON THE NONLINEARITIES OF LIFE 145

letters on their keyboard arranged in a non-optimal manner, as a matter
of fact in such a non-optimal manner as to slow down the typing rather
than make the job easy, in order to avoid jamming the ribbons as they
were designed for less electronic days. Therefore, as we started building
better typewriters and computerized word processors, several attempts
were made to rationalize the computer keyboard, to no avail. People
were trained on a QWERTY keyboard and their habits were too sticky
for change. Just like the helical propulsion of an actor into stardom,
people patronize what other people like to do. Forcing a rational
dynamic on the process would be superfluous, nay, impossible. This is
called a path dependent outcome , and has thwarted many mathematical
attempts at modeling behavior.

It is obvious that the information age, by homogenizing our tastes, is
causing the unfairness to be even more acute - those who win capture
almost all the customers. The example that strikes most as the most
spectacular lucky success is that of the software maker Microsoft and its
moody founder Bill Gates. While it is hard to deny that Gates is a man
of high personal standards, work ethics, and above average intelligence,
is he the best? Does he deserve it? Clearly not. Most people are equipped
with his software (like myself) because other people are equipped with
his software, a purely circular effect (economists call that “network
externalities”). Nobody ever claimed that it was the best software
product. Most of Gates’s rivals have an obsessive jealousy of his success.
There are maddened by the fact that he managed to win so big while
many of them are struggling to make their companies survive.

Such ideas go against classical economic models, in which results
either come from a precise reason (there is no account for uncertainty)
or the good guy wins (the good guy is the one who is more skilled and
has some technical superiority). Economists discovered path-dependent
effects late in their game, then tried to publish wholesale on the topic
that otherwise would be bland and obvious. For instance, Brian Arthur,
an economist concerned with nonlinearities at the Santa Fe Institute,
wrote that chance events coupled with positive feedback rather than
technological superiority will determine economic superiority - not
some abstrusely defined edge in a given area of expertise. While early
economic models excluded randomness, Arthur explained how
“unexpected orders, chance meetings with lawyers, managerial whims

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. . . would help determine which ones achieved early sales and, over
time, which firms dominated”.

Mathematics Inside and Outside the Real World

A mathematical approach to the problem is in order. While in
conventional models (such as the well-known Brownian random walk
used in finance) the probability of success does not change with every
incremental step, only the accumulated wealth, Arthur suggests models
such as the Polya process, which is mathematically very difficult to work
with, but can be easily understood with the aid of a Monte Carlo
simulator. The Polya process can be presented as follows: assume an urn
initially containing equal quantities of black and red balls. You are to
guess each time which color you will pull out before you make the draw.
Here the game is rigged. Unlike a conventional urn, the probability of
guessing correctly depends on past success, as you get better or worse at
guessing depending on past performance. Thus the probability of
winning increases after past wins, that of losing increases after past
losses. Simulating such a process, one can see a huge variance of
outcomes, with astonishing successes and large number of failures (what
we called skewness).

Compare such a process with those that are more commonly
modeled, that is, an urn from which the player makes guesses with
replacement. Sa/you played roulette and won. Would this increase your
chances of winning again? No. In a Polya process case, it does. Why is
this so mathematically hard to work with? Because the notion of
independence (i.e., when the next draw does not depend on past
outcomes) is violated. Independence is a requirement for working with
the (known) math of probability.

What has gone wrong with the development of economics as a
science? Answer: there was a bunch of intelligent people who felt
compelled to use mathematics just to tell themselves that they were
rigorous in their thinking, that theirs was a science. Someone in a great
rush decided to introduce mathematical modeling techniques (culprits:

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Leon Walras, Gerard Debreu, Paul Samuelson) without considering the
fact that either the class of mathematics they were using was too
restrictive for the class of problems they were dealing with, or that
perhaps they should be aware that the precision of the language of
mathematics could lead people to believe that they had solutions when
in fact they had none (recall Popper and the costs of taking science too
seriously). Indeed the mathematics they dealt with did not work in the
real world, possibly because we needed richer classes of processes - and
they refused to accept the fact that no mathematics at all was probably
better.

The so-called complexity theorists came to the rescue. Much
excitement was generated by the works of scientists who specialized
in nonlinear quantitative methods - the Mecca of those being the Santa
Fe Institute near Santa Fe, New Mexico. Clearly these scientists are
trying hard, and providing us with wonderful solutions in the physical
sciences and better models in the social siblings (though nothing
satisfactory there yet). And if they ultimately do not succeed, it will
simply be because mathematics may be of only secondary help in our
real world. Note another advantage of Monte Carlo simulations is that
we can get results where mathematics fails us and can be of no help. In
freeing us from equations it frees us from the traps of inferior
mathematics. As I said in Chapter 4, mathematics is merely a way of
thinking and meditating, little more, in our world of randomness.

BURIDAN’s donkey or the good side of randomness

Nonlinearity in random outcomes is sometimes used as a tool to break
stalemates. Consider the problem of the nonlinear nudge. Imagine a
donkey equally hungry and thirsty placed at exactly equal distance from
two sources of food and water. In such a framework, he would die of
both thirst and hunger as he would be unable to decide which one to get
to first. Now inject some randomness in the picture, by randomly
nudging the donkey, causing him to get closer to one source, no matter
which, and accordingly away from the other. The impasse would be
instantly broken and our happy donkey will be either in turn well fed
then well hydrated, or well hydrated then well fed.

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The reader no doubt has played a version of Buridan’s donkey, by
“flipping a coin” to break some of the minor stalemates in life where one
lets randomness help with the decision process. Let Lady Eortuna make
the decision and gladly submit. I often use Buridan’s donkey (under its
mathematical name) when my computer goes into a freeze between two
alternatives (to be technical, these “randomizations” are frequently done
during optimization problems, when one needs to perturbate a
function).

Note that Buridan’s donkey was named after the fourteenth-century
philosopher Jean Buridan. Buridan had an interesting death (he was
thrown in the Seine tied in a bag and died drowning). This tale was
considered an example of sophistry by his contemporaries who missed
the import of randomization - Buridan was clearly ahead of his time.

When It Rains, It Pours

As I am writing these lines, I am opening my fund to investors and
exploring how to raise money. I am suddenly realizing that the world’s
bi-polarity is hitting me very hard. Either one succeeds wildly, by
attracting all the cash, or fails to draw a single penny. Likewise with
books. Either everyone wants to publish it, or nobody is interested in
returning telephone calls (in the latter case my discipline is to delete the
name from my address book). This is making me, with my profound and
antiquated Mediterranean sense of metrion (measure) extremely
uncomfortable, even queasy. Too much success is the enemy (think of
the punishment meted out on the rich and famous), too much failure is
demoralizing. I would like the option of having neither.

RANDOMNESS AND OUR BRAIN. WE

On the difficulty of thinking of your vacation as a linear
combination of Paris and the Bahamas. Nero Tulip may never
ski in the Alps again. Some discussion of behavioral discoveries.

Some manifestations of probability blindness taken out of a
textbook. A little more on journalistic pollution. Why you may
be dead by now.

Paris or the Bahamas?

Y ou have two options for your next brief vacation in March. The
first is to fly to Paris; the second is to go to the Caribbean. You
expressed indifference between the two options; your spouse will tip the
decision one way or the other. Two distinct and separate images come
to you when you think of the possibilities. In the first one, you see
yourself standing at the Musee d’Orsay in front of some Pissaro
painting depicting a cloudy sky - the gray Parisian wintry sky. You are
carrying an umbrella under your arm. In the second image, you are
lying on a towel with a stack of books by your favorite authors next to
you (Tom Clancy and Amianus Marcellinus), and an obsequious waiter

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serving you a banana daiquiri. You know that the two states are
mutually exclusive (you can only be in one place at one time), but
exhaustive (there is a 100% probability that you will -be in one of
them). They are equiprobable, with, in your opinion, 50% probability
assigned to each.

You derive great pleasure thinking about your vacation; it motivates
you and makes your daily commute more bearable. But the adequate
way to visualize yourself, according to rational behavior under
uncertainty, is 50% in one of the vacation spots and 50% in the other
- what is mathematically called a linear combination of the two states.
Can your brain handle that? How desirable would it be to have your
feet in the Caribbean waters and your head exposed to the Parisian rain?
Our brain can properly handle one and only one state at once - unless
you have personality troubles of a deeply pathological nature. Now try
to imagine an 85%/15% combination. Any luck?

Consider a bet you make with a colleague for the amount of $1,000,
which, in your opinion, is exactly fair. Tomorrow night you will have
zero or $2,000 in your pocket, each with a 50% probability. In purely
mathematical terms, the fair value of a bet is the linear combination of
the states, here called the mathematical expectation, i.e., the
probabilities of each payoff multiplied by the dollar values at stake
(50% multiplied by 0 and 50% multiplied by $2,000 = $1,000). Can
you imagine (that is visualize, not compute mathematically) the value
being $1,000? We can conjure up one and only one state at a given time.
Left to our own devices, we are likely to bet in an irrational way, as one
of the states would dominate the picture.

Some Architectural Considerations

Time to reveal Nero’s secret. It was a black swan. He was then 35.
Although pre-war buildings in New York can have a pleasant front,
their architecture seen from the back offers a stark contrast by being
completely bland. The doctor’s examination room had a window
overlooking the backyard of one such Upper East side street, and Nero

RANDOMNESS AND OUR BRAIN: WE ARE PROBABILITY BLIND 151

will always remember how bland that backyard was in comparison with
the front, even if he were to live another half century. He will always
remember the view of the ugly pink backyard from the leaden window
panes, and the medical diploma on the wall that he read a dozen times
as he was waiting for the doctor to come into the room (half an eternity,
for Nero suspected that something was wrong). The news was then
delivered (grave voice), “I have some ... I got the pathology report . . .
It’s ... It is not as bad as it sounds ... It’s ... It’s cancer”. The
declaration caused his body to be hit by an electric discharge, running
through his back down to his knees. Nero tried to yell “what?” but no
sound came out of his mouth. What scared him was not so much the
news as the sight of the doctor. Somehow the news reached his body
before his mind. There was too much fear in the doctor’s eyes and Nero
immediately suspected that the news was even worse than what he was
being told (it was).

The night of the diagnosis, at the medical library where he sat,
drenched wet from walking for hours in the rain without noticing it and
making a puddle of water around him (he was yelled at by an attendant
but could not concentrate on what she was saying so she shrugged her
shoulders and walked away); later he read the sentence “72% 5-year
actuarially adjusted survival rate”. It meant that 72 people out of a
hundred make it. It takes between three and five years for the body
without clinical manifestations of the disease for the patient to be
pronounced cured (closer to three at his age). He then felt in his guts
quite certain that he was going to make it.

Now the reader might wonder about the mathematical difference
between a 28% chance of death and a 72% chance of survival over the
next five years. Clearly, there is none, but we are not made for
mathematics. In Nero’ mind a 28% chance of death meant the image of
himself dead, and thoughts of the cumbersome details of his funeral. A
72% chance of survival put him in a cheerful mood; his mind was
planning the result of a cured Nero skiing in the Alps. At no point
during his ordeal did Nero think of himself as 72% alive and 28%
dead.

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From Psychology to Neurobiology

For reasons we just saw, the laws of probability are said to be
counterintuitive by the researchers in the cognitive and behavioral
sciences. We are probability blind, these scientists say. This chapter will
rapidly illustrate some manifestations of such blindness, with a cursory
exposition of the research in that area.

The idea of probability blindness gave rise to an entire discipline
dedicated to the study of the effect these biases carry on our behavior. It
is filling out library shelves and causing the creation of numerous
investment funds dedicated to the sister idea that people do not behave
in a rational way in the markets. Some funds have been built around the
idea that people overreact to news, while others have been devoted to
the notion that, to the contrary, people underreact (I was told early in
my career that the more diversity the better for the market). These
beliefs give rise to two categories of trading strategies. On one side we
find the contrarians who subscribe to the following rationale: Hey, since
people systematically overreact, let us take the other side, sell the
winners and buy the losers. On the other side stand the momentum
players who do the exact opposite: Since markets do not adjust fast
enough, let us buy the winners and sell the losers. Because of
randomness, both categories will show periodic victories, which cannot
prove directly that either theory is right or wrong.

Even psychiatrists and clinical psychologists are joining the fray by
becoming “experts” - after all they know more about the human mind
that those financial economists with their unrealistic, unscientific
equations, and it is, after all, human behavior that ultimately influences
the markets. A yearly conference in Boston gathers medical doctors and
psychology researchers musing over market strategies. The idea may
seem simple, perhaps even boring until we encounter professionals,
whom we expect would deal with the matter with maximal expertise,
falling right into the trap like the man on the street.

RANDOMNESS AND OUR BRAIN- WE ARE PROBABILITY BLIND 153

OUR NATURAL HABITAT

I will not delve too deeply into amateur evolutionary theory to probe at
the reasons (besides, in spite of having spent some time in libraries I feel
that I am truly an amateur in the subject matter). Clearly, the
environment for which we have built our genetic endowment is not the
one that prevails today. I have not told too many of my colleagues that
their decision-making contains some lingering habits of cavemen - but
when markets experience an abrupt move, I experience the same rush of
adrenaline as if a leopard was seen prowling near my trading desk. Some
of my colleagues who break telephone handles upon losing money might
be even closer in their psychological makeup to our common origin.

This might be a platitude to those who frequent the Greek and Latin
classics, but we never fail to be surprised when noticing that people a
couple of dozen centuries removed from us can exhibit similar
sensibility and feelings. What used to strike me as a child upon visiting
museums is that ancient Greek statues exhibit men with traits
indistinguishable from ours (only more harmonious and aristocratic). I
was so wrong to believe that 2,200 years was a long time. Proust wrote
frequently about the surprise people have while coming across emotions
in Homeric heroes that are similar to those we experience today. By
genetic standards, these Homeric heroes of 30 centuries ago in all
likelihood have the exact identical genetic makeup as the pudgy middle-
aged man you see schlepping groceries in the parking lot. More than
that. In fact we are truly identical to the man who perhaps 80 centuries
ago started being called “civilized”, in that strip of land stretching from
Southeastern Syria to Southwestern Mesopotamia.

What is our natural habitat? By natural habitat, I mean the
environment in which we reproduced the most, the one in which we
spent the highest number of generations. The consensus among
anthropologists is that we have been around as a separate species for

130.000 years, most of which were spent in the African savannah. But we
do not have to go back that far in history to get the point. Imagine life in
an early urban settlement, in Middie-Town, Fertile Crescent, only about

3.000 years ago - surely modern times from a genetic standpoint.
Information is limited by the physical means of its transmission; one
cannot travel fast, hence information will come from faraway places in

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concise batches. Traveling is a nuisance fraught with all manner of
physical danger; you will settle within a narrow radius of where you were
born unless famine or some invading uncivilized tribe dislodges you and
your relatives from your happy settlement. The number of people you
would get to know in a lifetime will be small. Should a crime be
committed, it will be easy to gauge the evidence of guilt within the small
number of possible suspects. If you are unjustly convicted of a crime, you
will argue in simple terms, propounding simple evidence like “I was not
there as I was praying in the temple of Baal and was seen at dusk by the
high priest” and add that Obedshemesh son of Sahar was more likely to
be guilty because he had more to gain from the crime. Your life would be
simple, hence your space of probabilities would be narrow.

The real problem is, as I have mentioned, that such a natural habitat
does not include much information. An efficient computation of the
odds was never necessary until very recently. This explains why we had
to wait until the emergence of the gambling literature to see the growth
of the mathematics of probability. Popular belief holds that the religious
backdrop of the first and second millennium blocked the growth of tools
that hint at absence of determinism, and caused the delays in probability
research. The idea is extremely dubious; we simply did not compute
probabilities because we did not dare to? Surely the reason is rather
because we did not need to. Much of our problem comes from the fact
that we have evolved out of such a habitat faster, much faster than our
genes. Even worse; our genes have not changed at all.

’ KAFKA IN A COURTROOM

The O.J. Simpson trial provides an example of how our modern society
is ruled by probability (because of the explosion in information), while
important decisions are made without the smallest regard for its basic
laws. We are capable of sending a spacecraft to Mars, but we are
incapable of having criminal trials managed by the basic laws of
probability - yet evidence is clearly a probabilistic notion. I remember
buying a book on probability at a Borders Books chain bookstore only a
short distance from the Los Angeles courthouse where the “trial of the
century” was taking place - another book that crystallized the highly

RANDOMNESS AND OUR BRAIN-. WE ARE PROBABILITY BLIND 155

sophisticated quantitative knowledge in the field. How could such a leap
in knowledge elude lawyers and jurors only a few miles away?

People who are as close to being criminal as probability laws can
allow us to infer (that is with a confidence that exceeds the shadow of a
doubt ) are walking free because of our misunderstanding of basic
concepts of the odds. You could be convicted for a crime you never
committed owing to a poor reading of probability - for we still cannot
have a court of law properly compute the joint probability of events (the
probability of two events taking place at the same time). I was in a
dealing room with a TV set turned on when I saw one of the lawyers
arguing that there were at least four people in Los Angeles capable of
carrying O.J. Simpson’s DNA characteristics (thus ignoring the joint set
of events - we will see how in the next paragraph). I then switched off
the television set in disgust, causing an uproar among the traders. I was
under the impression until then that sophistry had been eliminated from
legal cases thanks to the high standards of republican Rome. Worse, one
Harvard lawyer used the specious argument that only 10% of men who
brutalize their wives go on to murder them, which is a probability
unconditional on the murder (whether the statement was made out of a
warped notion of advocacy, pure malice, or ignorance is immaterial).
Isn’t the law devoted to the truth? The correct way to look at it is to
determine the percentage of murder cases where women were killed by
their husband and had previously been battered by him (that is, 50%) -
for we are dealing with what is called conditional probabilities; the
probability that O.J. killed his wife conditional on the information of
her having been killed, rather than the unconditional probability of O.J.
killing his wife. How can we expect the untrained person to understand
randomness when a Harvard professor who deals and teaches the
concept of probabilistic evidence can make such an incorrect statement?

More particularly, where jurors (and lawyers) tend to make mistakes,
along with the rest of us, is in the notion of joint probability. They do
not realize that evidence compounds. The probability of my being
diagnosed with respiratory tract cancer and being run over by a pink
Cadillac in the same year, assuming each one of them is 1/100,000,
becomes 1/10,000,000,000 - by multiplying the two (obviously
independent) events. Arguing that O.J. Simpson had 1/500,000 chance
of not being the killer from the blood standpoint (the lawyers used the

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sophistry that there were four people with such blood types walking
around Los Angeles) and adding to it the fact that he was the husband of
the person and that there was additional evidence, then (owing to the
compounding effect) the odds against him rise to several trillion trillion.

“Sophisticated” people make worse mistakes. I can surprise people by
saying that the probability of the joint event is lower than either.
Behavioral economists submitted rational and educated people
(graduate students) to tests where they needed to produce the
probability of a young woman with a liberal arts education being a
bank teller or a feminist bank teller. They assigned on average a higher
probability to her being a feminist bank teller than to that of her being a
bank teller. I am glad to be a trader taking advantage of people’s biases
but I am scared of living in such a society.

AN ABSURD WORLD

Kafka’s prophetic book, The Trial, about the plight of a man, Joseph K.,
who is arrested for a mysterious and unexplained reason hit a spot as it
was written before we heard of the methods of the “scientific” totalitarian
regimes. It projected a scary future of mankind wrapped in absurd self-
feeding bureaucracies, with spontaneously emerging rules subjected to
the internal logic of the bureaucracy. It spawned an entire literature of the
absurd; the world may be too incongruous for us. I am terrified of certain
lawyers. After listening to statements during the O.J. trial (and their
effect) I was scared, truly scared of the possible outcome; my being
arrested for some- reason that made no sense probabilistically, and having
to fight some glib lawyer in front of a randomness illiterate jury.

We said that mere judgment would probably suffice in a primitive
society. It is easy for a society to live without mathematics - or traders to
trade without quantitative methods - when the space of possible out-
comes is one dimensional. One dimensional means that we are looking at
one sole variable, not a collection of separate events. The price of one
security is one dimensional, whereas the collection of the prices of several
securities is multidimensional and requires mathematical modeling - we
cannot easily see the collection of possible outcomes of the portfolio with
a naked eye, and cannot even represent it on a graph as our physical

RANDOMNESS AND OUR BRAIN: WE ARE PROBABILITY BLIND 157

world has been limited to visual representation in three dimensions only.
We will argue later why we run the risk of having bad models
(admittedly, we have) or making the error of condoning ignorance -
swinging between the Carybde of the lawyer who knows no math to the
Scylla of the mathematician who misuses his math because he does not
have the judgment to select the right model. In other words, we will have
to swing between the mistake of listening to the glib nonsense of a lawyer
who refuses science and that of applying the flawed theories of some
economist who takes his science too seriously. The beauty of science is
that it makes an allowance for both error types. Luckily, there is a middle
road - but sadly, it is rarely traveled.

KAHNEMAN AND TVERSKY

Who are the most influential economists of the century, in terms of
journal references, their followings, and their influence over the
profession? No, it is not John Maynard Keynes, not Alfred Marshall,
not Paul Samuelson, and certainly not Milton Friedman. They are
Daniel Kahneman and Amos Tversky, psychology researchers whose
specialty was to uncover areas where human beings are not endowed
with rational thinking and optimal economic behavior.

The pair taught us a lot about the way we perceive and handle
uncertainty. Their research, conducted on a population of students and
professors in the early 1970s, showed that we do not correctly
understand contingencies. Furthermore, they showed that in the rare
cases when we understand probability, we do not seem to consider it in
our behavior. Since the Kahneman and Tversky results, an entire
discipline called behavioral finance and economics has flourished. It is in
open contradiction with the orthodox so-called neoclassical economics
taught in business schools under the normative names of efficient
markets, rational expectations, and other such concepts. It is worth
stopping, at this juncture, and discussing the distinction between
normative and positive sciences. A normative science (clearly a self-
contradictory concept) offers prescriptive teachings; it studies how
things should be. Some economists, for example, (those of the efficient
market religion) believe that humans are rational and act rationally

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because it is the best thing for them to do (it is mathematically
“optimal”). The opposite is a positive science, which is based on how
people actually are observed to behave. In spite of economists’ envy of
physicists, physics is an inherently positive science while economics,
particularly microeconomics and financial economics, is predominantly
a normative one.

NEUROBIOLOGY

The soft sciences of psychology and economics have cheated us on
occasions in the past. How? Economics has produced laughable ideas,
ideas that evaporate once one changes the assumptions a little bit. It
seems difficult to take sides with bickering economists trading often-
incomprehensible arguments (even to economists). Biology and
medicine, on the other hand, rank higher in scientific firmness; like
true sciences, they can explain things while at the same time being
subjected to falsification. They are both positive and their theories are
better theories, that is, more easily testable. The good news is that
neurologists are starting to confirm these results, with what is called
environment mapping in the brain, by taking a patient whose brain is
damaged in one single spot (say, by a tumor or an injury deemed to be
local) and deducing by elimination the function performed by such part
of the anatomy. This isolates the parts of the brain that perform the
various functions. The Kahneman and Tversky results thus found a terra
firma with the leaps in our knowledge obtained through behavioral
genetics and, ftirther, plain medicine. Some of the physiology of our
brain makes us perceive things and behave in a given manner. We are,
whether we like it or not, prisoners of our biology.

Researchers in evolutionary psychology provide convincing reasons
for these biases. We have not had the incentive to develop an ability to
understand probability because we did not have to do so - but the more
profound reason is that we are not designed to understand things. We
are built only to survive and procreate. To survive, we need to overstate
some probabilities, such as those that can affect our survival. For
instance, those whose brain imparted higher odds to dangers of death, in
other words the paranoid, survived and gave us their genes (provided

RANDOMNESS AND OUR BRAIN: WE ARE PROBABILITY BLIND 159

such paranoia did not come at too high a cost, otherwise it would have
been a drawback). Our brain has been wired with biases that may
hamper us in a more complex environment, one that requires a more
accurate assessment of probabilities.

The story of these biases is thus being corroborated by the various
disciplines; the magnitude of the perceptional distortions makes us less
than rational, in the sense of both having coherent beliefs (i.e. free of
logical contradictions) and acting in a manner compatible with these
beliefs.

EXAMPLES OF BIASES IN UNDERSTANDING PROBABILITY

I found in the behavioral literature at least 40 damning examples of such
acute biases. Below is the account of a well-known test, and an embar-
rassing one for the medical profession. The following quiz was given to
medical doctors (which I borrowed from the excellent Deborah
Bennett’s Randomness).

A test of a disease presents a rate of 5% false positives. The disease
strikes 1/1,000 of the population. People are tested at random,
regardless of whether they are suspected of having the disease. A
patient’s test is positive. What is the probability of the patient being
stricken with the disease ? w

Most doctors answered 95%, simply taking into account the fact that
the test has a 95% accuracy rate. The answer is the conditional
probability that the patient is sick and the test shows it - close to 2%.
Less than one in five professionals got it right.

I will simplify the answer. Assume no false negatives. Consider that
out of 1,000 patients who are administered the test, one will be expected
to be afflicted with the disease. Out of a population of the remaining
999 healthy patients, the test will identify about 50 with the disease (it is
95% accurate). The correct answer should be that the probability of
being afflicted with the disease for someone selected at random who
presented a positive test is the following ratio:

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Number of afflicted persons
Number of true and false positives

here 1 in 51.

Think of the number of times you will be given a medication that
carries damaging side effects for a given disease you were told you had,
when you may only have 2% probability of being afflicted with it!

WE ARE OPTION BLIND

As an option trader, I have noticed that people tend to undervalue
options as they are usually unable to correctly mentally evaluate instru-
ments that deliver an uncertain payoff, even when they are fully con-
scious of the mathematics. Even regulators reinforce such ignorance by
explaining to people that options are a decaying or wasting asset.
Options that are out of the money are deemed to decay, by losing their
premium between two dates.

I will clarify next with a simplified (but sufficient) explanation of
what an option means. Say a stock trades at $100 and that someone
gives me the right (but not the obligation) to buy it at $110 one month
ahead of today. This is dubbed a call option. It only makes sense for me
to exercise it, by asking the seller of the option to deliver me the stock at
$110, if it trades at a higher price than $110 in one month’s time. If the
stock goes to $120, my option will be worth $10, for I will be able to
buy the stock at $110 from the option writer and sell it to the market at
$120, pocketing the difference. But this does not have a very high
probability. It is called out-of-the-money, for I have no gain from
exercising it right away.

Consider that I buy the option for $1. What do I expect the value of
the option to be one month from now? Most people think 0. That is not
true. The option has a high probability, say 90% of being worth 0 at
expiration, but perhaps 10% probability to be worth an average of $10.
Thus, selling the option to me for $1 does not provide the seller with
free money. If the sellers had instead bought the stock themselves at
$100 and waited the month, they could have sold it for $120. Making
$1 now was hardly, therefore, free money. Likewise, buying it is not a

RANDOMNESS AND OUR BRAIN: WE ARE PROBABILITY BLIND 161

wasting asset. Even professionals can be fooled. How? They confuse the
expected value and the most likely scenario (here the expected value is
$1 and the most likely scenario is for the option to be worth 0). They
mentally overweigh the state that is the most likely, namely, that the
market does not move at all. The option is simply the weighted average
of the possible states the asset can take.

There is another type of satisfaction provided by the option seller. It
is the steady return and the steady feeling of reward - what
psychologists call flow. It is very pleasant to go to work in the morning
with the expectation of being up some small money. It requires some
strength of character to accept the expectation of bleeding a little, losing
pennies on a steady basis even if the strategy is bound to be profitable
over longer periods. I noticed that very few option traders can maintain
what I call a “long volatility” position, namely a position that will most
likely lose a small quantity of money at expiration, but is expected to
make money in the long run because of occasional spurts. I discovered
very few people who accepted losing $1 for most expirations and
making $10 once in a while, even if the game were fair (i.e., they made
the $10 more than 10% of the time).

I divide the community of option traders into two categories:
premium sellers and premium buyers. Premium sellers (also called
option sellers) sell options, and generally make steady money, like John
in Chapters 1 and 5. Premium buyers do the reverse. Option sellers, it is
said, eat like chickens and go to the bathroom like elephants. Alas, most
option traders I encountered in my career are premium sellers - when
they blow up it is generally other people’s money.

How could professionals seemingly aware of the (simple)
mathematics be put in such a position? Our understanding of math
can remain quite superficial; medicine is starting to believe that our
actions are not quite guided by the parts of our brain that dictate
rationality (see Antonio Damasio’s Descartes’ Error or Ledoux’s
Emotional Brain 11 ). We think with our emotions and there is no way
around it. For the same reason, people who are otherwise rational
engage in smoking or in fights that get them no immediate benefits,
likewise people sell options even when they know that it is not a good
thing to do. But things can get worse. There is a category of people,
generally academics, who, instead of fitting their actions to their brains,

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instead fit their brains to their actions. These go back and cheat with the
statistics to justify their actions. In my business, they fool themselves
with statistical arguments to justify their option selling. .

Probabilities and the Media (More Journalists)

A journalist is trained in methods to express himself rather than to
plumb the depth of things - the selection process favors the most
communicative, not necessarily the most knowledgeable. My medical
doctor friends claim that many medical journalists do not understand
anything about medicine and biology, often making mistakes of a very
basic nature. I cannot confirm such statements, being myself a mere
amateur (though at times a voracious reader) in medical research but I
have noticed that they almost always misunderstand the probabilities
used in medical research announcements. The most common one
concerns the interpretation of evidence. They most commonly get mixed
up between absence of evidence and evidence of absence, a similar
problem to the one we saw in Chapter 9. How? Say I test some
chemotherapy, say Fluorouracil for upper respiratory tract cancer, and
find that it is better than a placebo, but only marginally so; that (in
addition to other modalities) it improves survival from 21 per 100 to 24
per 100. Given my sample size, I may not be confident that the
additional 3% survival points come from the medicine; it could be
merely attributable to randomness. I would write a paper outlining my
results and saying that there is no evidence of improved survival (as yet)
from such medicine, and that further research would be needed. A
medical journalist would pick it up and claim that one Professor N.N.
Taleb found evidence that Fluorouracil does not help, which is entirely
opposite to my intentions. Some naive doctor in Smalltown, even more
uncomfortable with probabilities than the most untrained journalist,
would pick it up and build a mental block against the medication, even
when some researcher finally finds fresh evidence that such medicine
confers a clear survival advantage.

RANDOMNESS AND OUR BRAIN: WE ARE PROBABILITY BLIND 163

CNBC AT LUNCH TIME

The advent of the financial television channel CNBC presented plenty of
benefits to the financial community but it also allowed a collection of
extrovert practitioners long on theories to voice them in a few minutes of
television time. One often sees respectable people making ludicrous (but
smart-sounding) statements about properties of the stock market. Among
these are statements that blatantly violate the laws of probability. One
summer during which I was assiduous at the health club, I often heard
such statement as “the real market is only 10% off the highs while the
average stock is close to 40% off its highs”, which is intended to be
indicative of deep troubles or anomalies - some harbinger of bear markets.

There is no incompatibility between the fact that the average stock is
down 40% from the highs while the average of all stocks (that is, the
market) is down 10% from its own highs. One must consider that the
stocks did not all reach their highs at the same time. Given that stocks
are not 100% correlated, stock A might reach its maximum in January,
stock B might reach its maximum in April, but the average of the two
stocks A and B might reach its maximum at some time in February.
Furthermore, in the event of negatively correlated stocks, if stock A is at
its maximum when stock B is at its minimum, then they could both be
down 40% from their maximum when the stock market is at its highs!
By a law of probability called distribution of the maximum of random
variables, the maximum of an average is necessarily less volatile than the
average maximum.

YOU SHOULD BE DEAD BY NOW

This brings to mind another common violation of probability by prime-
time T.V. financial experts, who may be selected for their looks,
charisma and their presentation skills, but certainly not for their incisive
minds. For instance, a fallacy that I saw commonly made by a
prominent T.V. financial guru goes as follows: “The average American
is expected to live 73 years. Therefore if you are 68 you can expect to
live five more years, and should plan accordingly”. She went into precise
prescriptions of how the person should invest for a five more years

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horizon. Now what if you are 80? Is your life expectancy minus seven
years? What these journalists confuse is the unconditional and
conditional life expectancy. At birth, your unconditional life expectancy
may be 73 years. But as you advance in age and do not die, your life
expectancy increases along with your life. Why? Because the other
people by dying have taken your spot in the statistics, for expectation
means average. So if you are 73 and are in good health, you may still
have, say, nine years in expectation. But the expectation would change,
and at 82, you will have another five years, provided of course you are
still alive. Even someone 100 years old still has a positive conditional life
expectation. Such a statement, when one thinks about it, is not too
different from the one that says: our operation has a mortality rate of
1%. So far we have operated on 99 patients with great success ; you are
our 1 00th, hence you have a 1 00% probability of dying on the table.

T.V. financial planners may confuse a few people. This is quite
harmless. What is far more worrying is the supply of information by non-
professionals to professionals; it is to the journalists that we turn next.

THE BLOOMBERG EXPLANATIONS

I have, on my desk, a machine eponymously called a Bloomberg™ (after
the legendary founder Michael Bloomberg). It acts as a safe e-mail
service, a news service, a historical data retrieving tool, a charting
system, an invaluable analytical aid and, not least, a screen where I can
see the price of securities and currencies. I have gotten so addicted to it
that I cannot operate without it, as I would otherwise feel cut off from
the rest of the world. I use it to get in contact with my friends, confirm
appointments, and solve some of those entertaining quarrels that put
some sharpness into life. Somehow, traders who do not have a
Bloomberg address do not exist for us (they have to have recourse to
the more plebeian internet). But there is one aspect of Bloomberg I would .
dispense with; the journalist’s commentary. Why? Because they engage
in explaining things and perpetuate the right-column, left-column
confusion in a serious manner. Bloomberg is not the sole perpetrator;
it is just that I have not been exposed to newspapers’ business sections
over the past decade, preferring to read real prose instead.

RANDOMNESS AND OUR BRAIN: WE ARE PROBABILITY BLIND 165

As I am writing these lines I see the following headlines on my
Bloomberg:

— * Dow is up 1.03 on lower interest rates.

— > Dollar down 0.12 yen on higher Japanese surplus.

and so on for an entire page. If I translate it well, the journalist claims to
provide an explanation for something that amounts to perfect noise. A
move of 1.03 with the Dow at 11,000 constitutes less than a 0.01%
move. Such a move does not warrant an explanation. There is nothing
there that an honest person can try to explain; there are no reasons to
adduce. But like apprentice professors of comparative literature,
journalists being paid to provide explanations will gladly and readily
provide them. The only solution is for Michael Bloomberg to stop
paying his journalists for providing commentary.

Significance-, how did I decide that it was perfect noise? Take a simple
analogy. If you engage in a mountain bicycle race with a friend across
Siberia and, a month later, beat him by one single second, you clearly
cannot quite boast that you are faster than him. You might have been
helped by something,, or it can be just plain randomness, nothing else.
That second is not in itself significant enough for someone to draw
conclusions. I would not write in my pre-bed-time diary: cyclist A is
better than cyclist B because he is fed with spinach whereas cyclist B has
2 diet rich in tofu. The reason I am making this inference is because he
beat him by 1.3 seconds in a 3,000 mile race. Should the difference be
one week, then I could start analyzing whether tofu is the reason, or if
there are other factors.

Causality: there is another problem; even assuming statistical
significance, one has to accept a cause and effect, meaning that the
event in the market can be linked to the cause proffered. Post hoc ergo
propter hoc (it is the reason because it came after). Say Hospital A
delivered 52% of boys and Hospital B delivered the same year only
48%; would you try to give the explanation that you had a boy because
it was delivered in hospital A?

Causality can be very complex. It is very difficult to isolate a single
cause when there are plenty around. This is called multivariate analysis.
For instance, if the stock market can react to U.S. domestic interest

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rates, the dollar against the yen, the dollar against the European
currencies, the European stock markets, the United States balance of
payments, United States inflation, and another dozen prime factors,
then the journalists need to look at all of these factors, look at their
historical effect both in isolation and jointly, look at the stability of such
influence, then, after consulting the test statistic isolate the factor if it is
possible to do so. Finally, a proper confidence level needs to be given to
the factor itself; if it is less that 90% the story would be dead. I can
understand why Hume was extremely obsessed with causality and could
not accept such inference anywhere.

I have a trick to know if something real in the world is taking place. I
have set up my Bloomberg monitor to display the price and percentage
change of all relevant prices in the world: currencies, stocks, interest
rates, and commodities. By dint of looking at the same setup for years,
as I keep the currencies in the upper left corner and the various stock
markets on the right, I managed to build an instinctive way of knowing
if something serious is going on. The trick is to look only at the large
percentage changes. Unless something moves by more than its usual
daily percentage change, the event is deemed to be noise. Percentage
moves are the size of the headlines. In addition, the interpretation is not
linear; a 2% move is not twice as significant an event as 1%, it is rather
like four times. The headline of the Dow moving by 1.3 points on my
screen today has less than one millionth of the significance of the serious
7% drop of October 1997. People might ask me: why do 1 want
everybody to learn some statistics? The answer is that too many people
read explanations. We cannot instinctively understand the nonlinear
aspect of probability.

FILTERING METHODS

Engineers use methods to clean up the noise from the signal in the data.
Did it ever occur to you while talking to your cousin in Australia or the
South Pole that the static on the telephone line could be distinguished
from the voice of your correspondent? The method is to consider that
when a change in amplitude is small, it is more likely to result from
noise - with its likelihood of being a signal increasing exponentially as

RANDOMNESS AND OUR BRAIN: WE ARE PROBABILITY BLIND 167

Figure 11.1 Unfiltered Data Containing Signal and Noise.

its magnitude increases. The method is called a smoothing kernel which
has been applied in Figures 11.1 and 11.2. But our auditory system is
incapable of performing such a function by itself. Likewise our brain
cannot see the difference between a significant price change and mere
noise, particularly when it is pounded with unsmoothed journalistic
noise.

Figure 11.2 Same Data With its Noise Removed.

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WE DO NOT UNDERSTAND CONFIDENCE LEVELS

Professionals forget the following reality. It is not the estimate or the
forecast that matters so much as the degree of confidence with the
opinion. Consider that you are going on a trip one fall morning and
need to formulate an idea about the weather conditions prior to packing
your luggage. If you expect the temperature to be 60 degrees, plus or
minus 10 degrees (say in Arizona), then you would take no snow clothes
and no portable electric fan. Now what if you were going to Chicago,
where you are told that the weather, while being 60 degrees, will
nevertheless vary by about 30 degrees? You would have to pack winter
and summer clothes. Here the expectation of the temperature carries
little importance concerning the choice of clothing; it is the variance that
matters. Your decision to pack is markedly different now that you are
told that the variability would be around 30 degrees. Now let us push
the point further; what if you were going to a planet where the
expectation is also going to be around 60 degrees, but plus or minus 500
degrees? What would you pack?

We can see that my activity in the market depends far less on where I
think the market is going so much as it does on the degree of error I
allow around such a confidence level.

AN ADMISSION

We close this chapter with the following information: I consider myself
as prone to foolishness as anyone I know, in spite of my profession and
the time spent building my expertise on the subject. But here is the
exception; I know that I am very, very weak on that score. My humanity
will try to foil me; I have to stay on my guard. I was born to be fooled by
randomness. That will be explored in Part III.

O dysseus, the Homerian hero, had the reputation of using guile to
overcome stronger opponents. I find the most spectacular use of
such guile was against no other opponent than himself.

In book 12 of the Odyssey, the hero encounters the sirens, on an
island not far from the rocks of Caribde and Scylla. Their songs are
known to charm the sailors into madness, causing them to irresistibly-
cast themselves into the sea off the sirens’ coast, and perish. The
indescribable beauty of the sirens’ songs is contrasted with the
moldering corpses of sailors that strayed into the area around them.
Odysseus, forewarned by Circe, contrives the following ruse. He fills the
ears of all his men with wax, to the point of total deafness, and has
himself tied to the mast. The sailors are under strict instructions not to
release him. As they approach the sirens’ island, the sea is calm and over
the water comes the sound of a music so ravishing that Odysseus
struggles to get loose, expending an inordinate amount of energy to
unrestrain himself. His men tie him even further, until they are safely
past the poisoned sounds.

The first lesson I took from the story is not to even attempt to be
Odysseus. He is a mythological character and I am not. He can be tied
to the mast; I can merely reach the rank of a sailor who needs to have his
ears filled with wax.

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I AM NOT SO INTELLIGENT

The epiphany I had in my career in randomness came when I understood
that I was not intelligent enough, nor strong enough, to even try to fight
my emotions. Besides, I believe that I need my emotions to formulate my
ideas and get the energy to execute them.

I am just intelligent enough to understand that I have a predisposition
to be fooled by randomness - and to accept the fact that I am rather
emotional. I am dominated by my emotions - but as an aesthete, I am
happy about that fact. I am just like every single character whom I
ridiculed in this book. Not only that, but I may be even worse than them
because there may be a negative correlation between beliefs and
behavior (recall Popper the man). The difference between myself and
those I ridicule is that I try to be aware of it. No matter how long I study
and try to understand probability, my emotions will respond to a
different set of calculations, those that my unintelligent genes want me
to handle. If my brain can tell the difference between noise and signal,
my heart cannot.

Such unintelligent behavior does not just cover probability and
randomness. I do not think I am reasonable enough to avoid getting
angry when a discourteous driver blows his horn at me for being one
nanosecond late after a traffic light turns green. I am fully aware that
such anger is self-destructive and offers no benefit, and that if I were to
develop anger for every idiot around me doing something of the sort, I
would be long dead. These small daily emotions are not rational. But we
need them to function properly. We are designed to respond to hostility
with hostility. I have enough enemies to add some spice to my life, but I
sometimes wish I had a few more (I rarely go to the movies and need the
entertainment). Life would be unbearably bland if we had no enemies
on whom to waste efforts and energy.

The good news is that there are tricks. One such trick is to avoid eye
contact (through the rear-view mirror) with other persons in such
encounters as traffic situations. I try to imagine that the other person is a
Martian, rather than a human being. It works sometimes - but it works
best when the person presents the appearance of being from a different
species. How? I am an avid road cyclist. Recently, as I was riding along
with other cyclists, slowing down traffic in a rural area, a small woman

WAX IN MY EARS

173

in a giant sports utility vehicle opened her window and heaped curses at
us. Not only did it not upset me but I did not even interrupt my thoughts
to pay attention. When I am on my bicycle, people in large trucks
become a variety of dangerous animals, capable of threatening me but
incapable of making me angry.

I have, like anyone with strong opinions, a collection of critics among
finance academics and economists, annoyed by my attacks on their
misuse of probability and unhappy about my branding them as
pseudoscientists. I am incapable of taming my emotions when reading
their comments. The best I can do is just not read them. Likewise with
journalists. Not reading their discussions of markets spares me plenty of
emotional expenditure. I will do the same with reviews of this book.
Wax in my ears.

The Odyssean Mute Command

Recall that the accomplishment from which I derive the most pride is my
weaning myself from television and the news media. I am currently so
weaned that it actually costs me more energy to watch television than to
perform any other activity, like, say, writing this book. But this did not
come without tricks. Without tricks I would not escape the toxicity of
the information age. In the trading room of my company I currently
have the television set turned on all day with the financial news channel
CNBC staging commentator after commentator and CEO after CEO
murdering rigor all day long. What is the trick? I have the volume
turned completely off. Why? Because when the television set is silent,
the babbling person looks ridiculous, exactly the opposite effect as when
the sound is on. One sees a person with moving lips and contortions in
their facial muscles, taking themselves seriously - but no sound comes
out. We are visually but not auditorily intimidated, which causes a
dissonance. The speaker’s face expresses some excitement, but since no
sound comes out, the exact opposite is conveyed. This is the sort of
contrast the philosopher Henri Bergson had in mind in his Treatise on
Laughter, with his famous description of the gap between the

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seriousness of a gentleman about to walk on a banana skin and the
comical aspect of the situation. Television pundits lose their intimidat-
ing effect; they even look ridiculous. They seem to be excited about
something terribly unimportant. Suddenly pundits become clowns,
which is a reason the writer Graham Greene refused to go on television.

I had this idea of stripping people from language while, on a trip, I
listened (while brutally jetlagged) to a speech in Cantonese, a language I
do not understand, without the benefit of translation. Since I had no
possible clue about his subject, the animated orator lost a large share of
his dignity. The idea came to me that perhaps I could use a genetic bias,
here prejudice, to offset another genetic bias, our predisposition to take
information seriously. It seems to work.

This part, the conclusion of this book, presents the human aspect of
dealing with uncertainty. I have personally failed in a general insulation
from randomness, but I have managed a few tricks.

On gamblers’ ticks crowding up my life. Why bad taxi-cab
English can help you make money. How I am the fool of all
fools, except that I am aware of it. Dealing with my genetic
unfitness. No boxes of chocolate under my trading desk.

Taxi-Cab English and Causality

F irst, a flashback in time to my early days as a trader in New York.

Early in my career, I worked at Credit Suisse First Boston, then
located in the middle of the block between 52nd and 53rd Street,
between Madison and Park Avenue. It was called a Wall Street firm, in
spite of its midtown location - 1 used to claim to work “on Wall Street”
in spite of having been lucky enough to set foot only twice in the
physical Wall Street, one of the most repulsive areas I have visited east
of Newark, New Jersey.

Then, in my twenties, I lived in a book-choked (but otherwise rather
bare) apartment in Manhattan’s upper east side. The bareness was not
ideological; it was simply because I never managed to enter a furniture
store, as I would eventually stop at a bookstore along the way and haul

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bags of books instead. As can be expected, the kitchen was devoid of
any form of food and utensils, save for a defective expresso machine, as
I learned to cook only very recently (even then . . .).

I went to work every morning in a yellow cab, which dropped me off
at the corner of Park Avenue and 53rd Street. Cab drivers in New York
City are known to be rather untamed and universally unfamiliar with
the geography of the place, but, on occasion, one can find a cab driver
who can both be unacquainted with the city and skeptic of the
universality of the laws of arithmetic. One day I had the misfortune (or
perhaps the fortune, as we will see) to ride with a driver who did not
seem capable of handling any language known to me, which includes
taxi-cab English. I tried to help him navigate south between 74th Street
and 53rd Street, but he stubbornly continued the journey an additional
block south, forcing me to use the 52nd Street entrance. That day, my
trading portfolio made considerable profits, owing to considerable
turmoil in currencies; it was then the best day of my young career.

The next day, as usual, I hailed a cab from the corner of 74th Street
and Third Avenue. The previous driver was nowhere in sight, perhaps
deported back to the old country. Too bad; I was gripped with the
unexplainable desire to pay him back for the favor he had done me and
surprise him with a gigantic tip. Then I caught myself instructing the
new cab driver to take me to the north-east corner of 52nd Street and
Park Avenue, exactly where I was dropped off the day before. I was
taken aback by my own words . . . but it was too late.

When I looked at my reflection in the elevator’s mirror, it dawned on
me that I wore the exact same tie as the day before - with the coffee
stains from the previous day’s fracas (my only addiction is to coffee).
There was someone in me who visibly believed in a strong causal link
between my use of the entrance, my choice of tie and the previous day’s
market behavior. I was disturbed for acting like a fake, like an actor
who impersonated some role that was not his. I felt that I was an
impostor. On the one hand, I talked like someone with strong scientific
standards, a probabilist focused on his craft. On the other, I had closed
superstitions just like one of these blue-collar pit traders. Would I have
to go buy a horoscope next?

A little brooding revealed that my life until then had been governed
by mild superstitions, me the expert in options and dispassionate

GAMBLERS’ TICKS AND PIGEONS IN A BOX

177

calculator of probabilities, a rational trader! It was not the first time
that I had acted on mild superstitions of a harmless nature, which I
believed were instilled in me by my Eastern Mediterranean roots: one
does not grab the salt shaker from the hand of another person risking a
falling out; one is to knock on wood upon receiving a compliment; plus
many other Levantine beliefs passed on for a few dozen centuries. But
like many things that brew and spread around the ancient pond, these
beliefs I had taken with a fluctuating mixture of solemnity and mistrust.
We consider them more like rituals than truly important actions meant
to stave off undesirable turns of the goddess Fortuna - superstitions can
instill some poetry in daily life.

The worrying part was that it was the first time that I noticed
superstitions creeping into my professional life. My profession is to act
like an insurance company, stringently computing the odds based on
well defined methods, and making a profit because other people are less
rigorous, get blinded by some “analysis”, or act with the belief that they
are chosen by destiny. But there was too much randomness flooding my
occupation.

I detected the rapid accumulation of what is called “gamblers’ ticks”
surreptitiously developing in my behavior - though minute and barely
detectable. Until then these small ticks had escaped me. My mind
seemed to be constantly trying to detect a statistical connection between
some of my facial expressions and outcome of events. For example, my
income started to increase after I discovered my slight near-sightedness
and started wearing glasses. Although glasses were not quite necessary,
nor even useful, except for night driving, I kept them on my nose as I
unconsciously acted as if I believed in the association between
performance and glasses. To my brain such statistical association was
as spurious as it can get, owing to the reduced sample size, yet this
native statistical instinct did not seem to benefit from my expertise in
hypothesis testing.

Gamblers are known to develop some behavioral distortions as a
result of some pathological association between a betting outcome and
some physical move. “Gambler” is about the most derogatory term that
could be used in my derivatives profession. As an aside, gambling to me
is best defined as an activity where the agent gets a thrill when
confronting a random outcome, regardless of whether he has the odds

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stacked in his favor or against him. Even when the odds are clearly
stacked against the gambler, he sometimes transcends the odds by
believing that destiny selected him in some manner. This .shows in the
very sophisticated people one meets in casinos where they normally
should not be found. I even ran into world-class probability experts who
had a gambling habit on the side, throwing all of their knowledge to the
wind. For example, a former colleague of mine and one of the most
intelligent people I have ever met, frequently went to Las Vegas, and
seemed to be such a turkey that the casino provided him with
complimentary luxury suites and transportation. He even consulted a
fortune teller prior to taking large trading positions and tried to get
reimbursed by our employer.

The Skinner Pigeon Experiment

At 25, I was totally ignorant of the behavioral sciences. I had been
fooled by my education and culture into believing that my superstitions
were cultural, and that, consequently, they could be shed through the
exercise of so-called reason. Taken at the general level of society,
modern life would eliminate them as science and logic would enter it.
But in my case, I was over time getting more sophisticated intellectually,
but the floodgates of randomness were bursting and I was becoming
more superstitious.

These superstitions needed to be biological - but I was brought up in
an era when the dogma was that it was nurture, rarely nature, that was
the culprit. Clearly, there was nothing cultural about my link between
my wearing glasses and a random market outcome. There was nothing
cultural in my link between my use of entrance and my performance as a
trader. There was nothing cultural in my wearing the same tie as the day
before. Something in us has not developed properly over the past
thousand years and I was dealing with the remnant of our old brain.

To probe the point further, we need to look at such formations of
causal associations in the lower forms of life. The famous Harvard
psychologist B.F. Skinner constructed a box for rats and pigeons,

GAMBLERS’ TICKS AND PIGEONS IN A BOX

179

equipped with a switch that the pigeon can operate by pecking. In
addition, an electrical mechanism delivers food into the box. Skinner
designed the box in order to study more general properties of the
behavior of a collection of nonhumans, but it was in 1948 that he had
the brilliant idea of ignoring the lever and focusing on the food delivery.
He programmed it to deliver food at random to the famished birds.

He saw quite astonishing behavior on the part of the birds; they
developed an extremely sophisticated rain-dance type of behavior in
response to their ingrained statistical machinery. One bird swung its
head rhythmically against a specific corner of the box, others spun their
heads anti-clockwise; literally all of the birds developed a specific ritual
that progressively became hard-wired into their mind as linked to their
feeding.

This problem has a more worrying extension; we are not made to
view things as independent from each other. When viewing two events
A and B, it is hard not to assume that A causes B, B causes A, or both
cause each other. Our bias is immediately to establish a causal link.
While to a budding trader this causes hardly any worse costs than a few
pennies in cab fare, it can draw the scientist into spurious inference. For
it is harder to act as if one were ignorant than as if one were smart;
scientists know that it is emotionally harder to reject a hypothesis than
to accept it (what is called type I and type II errors) - quite a difficult
matter when we have such sayings as felix qui potuit cognoscere causas
(happy is he who understands what is behind things). It is very hard for
us to just shut up. We are not cut out for it. Popper or not, we take
•■hings too seriously.

Philostratus Redux

I offered no solution to the problem of statistical inference at a low
resolution. I discussed in Chapter 3 the technical difference between
noise and meaning - but it is time to discuss the execution. The Greek
philosopher Pyrrho, who advocated a life of equanimity and
indifference, was criticized for failing to keep his composure during a

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critical circumstance (he was chased by an ox). His answer was that he
found it sometimes difficult to rid himself of his humanity. If Pyrrho
cannot stop being human, I do not see why the rest of us should
resemble the rational man who acts perfectly under uncertainty as
propounded by economic theory. I discovered that much of the
rationally obtained results using my computations of the various
probabilities do not register deeply enough to impact my own conduct.
In other words, I acted like the doctor in Chapter 11 who knew of the
2% probability of the disease, but somehow unwittingly treated the
patient as if the ailment had a 95% probability of being there. My brain
and my instinct were not acting in concert.

The details are as follows. As a rational trader (all traders boast so) I
believe as I discussed before that there is a difference between noise and
signal, and that noise needs to be ignored while a signal needs to be
taken seriously. I use elementary (but robust) methods that allow me to
calculate the expected noise and signal composition of any fluctuation in
my trading performance. For example, after registering a profit of
$100,000 on a given strategy, I may assign a 2% probability to the
hypothesis of the strategy being profitable and 98% probability to the
hypothesis that the performance may be the result of mere noise. A gain
of $1,000,000, on the other hand, certifies that the strategy is a
profitable one, with a 99% probability. A rational person would act
accordingly in the selection of strategies, and set his emotions in
accordance with his results. Yet I have experienced leaps of joy over
results that I knew were mere noise, and bouts of unhappiness over
results that did not carry the slightest degree of statistical significance. I
cannot help itj but I am emotional and derive most of my energy from
my emotions. So the solution does not reside in taming my heart.

Since my heart does not seem to agree with my brain, I need to fake
serious action to avoid making irrational trading decisions, namely, by
denying myself access to my performance report unless it hits a
predetermined threshold. This is no different from the divorce between
my brain and my appetite when it comes to the consumption of
chocolate. I generally deal with it by ascertaining that there are no
chocolate boxes under my trading desk.

One of the most irritating conversations I’ve had is with people who
lecture me on how I should behave. Most of us know pretty much how

GAMBLERS’ TICKS AND PIGEONS IN A BOX

181

we should behave. It is the execution that is the problem, not the
absence of knowledge. I am tired of the moralizing slow-thinkers who
pound me with platitudes like I should floss daily, eat my regular apple
and visit the gym outside of the new-year resolution. In the markets the
recommendation would be to ignore the noise component in the
performance. We need tricks to get us there but before that we need to
accept the fact that we are mere animals in need of lower forms of tricks,
not lectures.

Finally, I consider myself lucky for not having a cigarette addiction.
For the best way to understand how we could be rational in our
perception of the risks and probabilities and, at the same time, be foolish
while acting on them, would be to have a conversation with a cigarette
smoker. For few cigarette smokers remain unaware of the fact that lung
cancer strikes one in three of their population. If you remain uncon-
vinced, take a look at the huddling smoking crowd outside the service
entrance of the Memorial-Sloan Kettering Cancer Center in New York
City’s upper East side. You will see dozens of cancer nurses (and,
perhaps, doctors) standing outside the entrance with a cigarette in hand
as hopeless patients are wheeled in for their treatments.

Cato the censor sends Carneades packing. Monsieur de Norpois
does not remember his old opinions. Beware the scientist.
Marrying ideas. The same Robert Merton helping the author
start his firm. Science evolves from funeral to funeral.

A sk your local mathematician to define probability; he would most
probably show you how to compute it. As we saw in Chapter 3 on
probabilistic introspection, probability is not about the odds, but about
the belief in the 'existence of an alternative outcome, cause, or motive.
Recall that mathematics is a tool to meditate, not compute. Again, let us
go back to the elders for more guidance - for probabilities were always
considered by them as nothing beyond a subjective, and fluid, measure
of beliefs.

CARNEADES COMES TO ROME: ON PROBABILITY AND SKEPTICISM 183

Carneades Comes to Rome

Around 155 B.C., the Greek post-classical philosopher Carneades of
Cyrene came to Rome as one of the three Athenian ambassadors who
came to beg the Roman Senate for a political favor. A fine had been
levied against the citizens of their city, and they wanted to convince
Rome that it was unfair. Carneades represented the Academy, the same
argumentative open-air institution where three centuries before Socrates
drove his interlocutors to murder him just to get some respite from his
arguments. It was now called the New Academy, was no less
argumentative, and had the reputation of being the hotbed of skepticism
in the ancient world.

On the much anticipated day of his oration, he stood up and
delivered a brilliantly argued harangue in praise of justice and how
devolving it should be at the top of our motives. The Roman audience
was spellbound. It was not just his charisma; the audience was swayed
by the strength of the arguments, the eloquence of the thought, the
purity of the language, and the energy of the speaker. But that was not
the point he wanted to drill.

The next day, Carneades came back, stood up and established the
doctrine of uncertainty of knowledge in the most possibly convincing
way. How? By proceeding to contradict and refute with no less swaying
arguments what he had established so convincingly the day before. He
managed to persuade the very same audience and in the same spot that
justice should be way down on the list of motivations for human
undertakings.

Now the bad news. Cato the elder (the “censor”) was among the
audience, already quite old, and no more tolerant than he had been
during his office of censor. Enraged, he persuaded the Senate to send the
three ambassadors packing lest their argumentative spirit muddle the
spirit of the youth of the Republic and weaken the military culture.
(Cato had banned during his office of censorship all Greek rhetoricians
from establishing residence in Rome. He was too much a no-nonsense
type of person to accept their introspective expansions.)

Carneades was not the first skeptic in classical times, nor was he the
first to teach us the true notion of probability. But this incident remains

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the most spectacular in its impact on generations of rhetoricians and
thinkers. Carneades was not merely a skeptic; he was a dialectician,
someone who never committed himself to any of the premises from
which he argued, or to any of the conclusions he drew from them. He
stood all his life against arrogant dogma and belief in one sole truth. Few
credible thinkers rival Carneades in their rigorous skepticism (a class that
would include the medieval Arab philosopher A1 Gazali, Hume, and
Kant - but only Popper came to elevate his skepticism to an all-encom-
passing scientific methodology). As the skeptics’ main teaching was that
nothing could be accepted with certainty, conclusions of various degrees
of probability could be formed, and these supplied a guide to conduct.

Stepping further back in time and searching for the first known uses
of probabilistic thinking in history, we find it harks back to sixth-
century (B.C.) Greek Sicily. There, the notion of probability was used in
a legal framework by the very first rhetoricians who, when arguing a
case, needed to show the existence of a doubt concerning the certainty
of the accusation. The first known rhetorician was a Syracusean named
Korax who engaged in teaching people how to argue from probability.
At the core of his method was the notion of the most probable. For
example, the ownership of a piece of land, in the absence of further
information and physical evidence, should go to the person after whose
name it is best known. One of his indirect students, Gorgias, took this
method of argumentation to Athens, where it flourished. It is the
establishment of such most probable notions that taught us to view the
possible contingencies as distinct and separable events with probabilities
attached to each one of them.

PROBABILITY THE CHILD OF SKEPTICISM

Until the Mediterranean basin was dominated with monotheism, which
led to the belief in some form of uniqueness of the truth (to be
superceded later by episodes of communism), skepticism had gained
currency among many major thinkers - and certainly permeated the
world. The Romans did not have a religion per se; they were too
tolerant to accept a given truth. Theirs were a collection of a variety of
flexible and syncretic superstitions. I will not get too theological, except

CARNEADES COMES TO ROME: ON PROBABILITY AND SKEPTICISM 185

to say that we had to wait for a dozen centuries in the Western world to
espouse critical thinking again. Indeed, for some strange reason during
the middle ages, Arabs were critical thinkers (through their post-
classical philosophical tradition) when Christian thought was dogmatic,
then after the renaissance, the roles mysteriously reversed.

One author from antiquity who provides us evidence of such thinking
is the garrulous Cicero. He preferred to be guided by probability than
allege with certainty - very handy, some said, because it allowed him to
contradict himself. This may be a reason for us, who have learned from
Popper how to remain self critical, to respect him more, as he did not
hew stubbornly to an opinion for the mere fact that he had voiced it in
the past. Indeed your average literature professor would fault him for
his contradictions and his change of mind.

It was not until modern times that such desire to be free from our
own past statements emerged. Nowhere was it made more eloquently
than in rioting student graffiti in Paris. The student movement that took
place in France in 1968, with the youth no doubt choking under the
weight of years of having to sound intelligent and coherent, produced,
among other jewels, the following demand:

We demand the right to contradict ourselves!

Monsieur de Norpois’ s Opinions

Modern times provide us with a depressing story. Self-contradiction is
made culturally to be shameful, a matter that can prove disastrous in
science. Marcel Proust’s novel In Search of Time Lost features a semi-
retired diplomat, Marquis de Norpois, who, like all diplomats before
the advent of the fax machine, was a socialite who spent considerable
time in salons. The narrator of the novel sees Monsieur de Norpois
openly contradicting himself on some issue (some prewar rapproche-
ment between France and Germany). When reminded of his previous
position, Monsieur de Norpois did not seem to recall it. Proust reviles
him:

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Monsieur de Norpois was not lying. He had just forgotten. One
forgets rather quickly what one has not thought about with depth,
what has been dictated to you by imitation, by _ the passions
surrounding you. These change, and with them so do your memories.
Even more than diplomats, politicians do not remember opinions
they had at some point in their lives and their fibbings are more
attributable to an excess of ambition than a lack of memory.

Monsieur de Norpois is made to be ashamed of the fact that he
expressed a different opinion. Proust did not consider that the diplomat
might have changed his mind. We are supposed to be faithful to our
opinions. One becomes a traitor otherwise.

Now I hold that Monsieur de Norpois should be a trader. One of the
best traders I have ever encountered in my life, Nigel Babbage, has the
remarkable attribute of being completely free of any path dependence in
his beliefs. He exhibits absolutely no embarrassment buying a given
currency on a pure impulse, when only hours ago he might have voiced
a strong opinion as to its future weakness. What changed his mind? He
does not feel obligated to explain it.

The public person most visibly endowed with such a trait is George
Soros. One of his strengths is that he revises his opinion rather rapidly,
without the slightest embarrassment. The following anecdote illustrates
Soros’s ability to reverse his opinion in a flash. The French playboy trader
Jean-Manuel Rozan discusses the following episode in his auto-
biography 12 (disguised as a novel in order to avoid legal bills). The
protagonist (Rozan) used to play tennis in the Hamptons on Long Island
with Georgi Saulos, an “older man with a funny accent”, and sometimes
engage in discussions about the market, not initially knowing how
important and influential Saulos truly was. One week-end, Saulos
exhibited in his discussion a large amount of bearishness, with a com-
plicated series of arguments that the narrator could not follow. He was
obviously short the market. A few days later, the market rallied violently,
making record highs. The protagonist worried about Saulos, asked him at
their subsequent tennis encounter if he was hurt. “We made a killing”,
Saulos said. “I changed my mind. We covered and went very long”.

It was this very trait that, a few years later, affected Rozan negatively
and almost cost him a career. Soros gave Rozan in the late 1980s 20

CARNEADES COMES TO ROME: ON PROBABILITY AND SKEPTICISM 187

million dollars to speculate with (a sizeable amount at the time), which
allowed him to start a trading company (I was almost dragged into it). A
few days later, as Soros was visiting Paris, they discussed markets over
lunch. Rozan saw Soros becoming distant. He then completely pulled
the money, offering no explanation. What characterizes real
speculators like Soros from the rest is that their activities are devoid
of path dependence. They are totally free from their past actions. Every
day is a clean slate.

PATH DEPENDENCE OF BELIEFS

There is a simple test to define path dependence of beliefs. Say you own
a painting you bought for $20,000, and owing to rosy conditions in the
art market, it is now worth $40,000. If you owned no painting, would
you still acquire it at the current price? If you would not, then you are
said to be married to your position. There is no rational reason to keep a
painting you would not buy at its current market rate - only an
emotional investment. Many people get married to their ideas all the
way to the grave. Beliefs are said to be path dependent if the sequence of
ideas is such that the first one dominates.

There are reasons to believe that, for evolutionary purposes, we may
be programmed to build a loyalty to ideas in which we have invested
time. Think about the consequences of being a good trader outside of
the market activity, and deciding every morning at 8 a.m. whether to
keep the spouse or if it is not better to part with him or her for a better
emotional investment elsewhere. Or think of a politician who is so
rational that, during a campaign, he changes his mind on a given matter
because of fresh evidence and abruptly switches political parties. That
would make rational investors who evaluate trades in a proper way a
genetic oddity - perhaps a rare mutation. Some medical researchers find
that purely rational behavior on the part of humans is a sign of a defect
in the amygdala, that the subject is, literally, a psychopath. Could Soros
have a genetic flaw that makes him rational as a decision maker?

Such trait of absence of marriage to ideas is indeed rare among
humans. Just as we do with children, we support those in whom we have
i heavy investment of food and time until they are able to propagate our

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genes, so we do with ideas. An academic who became famous for
espousing an opinion is not going to voice anything that can possibly
devalue his own past work and kill years of investment. People who
switch parties become traitors, renegades, or, worst of all, apostates
(those who abandoned their religion were punishable by death).

Computing Instead of Thinking

There is another story of probability other than the one I introduced
with Carneades and Cicero. Probability entered mathematics with
gambling theory, and stayed there as a mere computational device.
Recently, an entire industry of “risk measurers” emerged, specializing in
the application of these probability methods to assess risks in the social
sciences. Clearly, the odds in games where the rules are clearly and
explicitly defined are computable and the risks consequently measured.
But not in the real world. For mother nature did not endow us with clear
rules. The game is not a deck of cards (we do not even know how many
colors there are). But somehow people “measure” risks, particularly if
they are paid for it. I have already discussed Hume’s problem of
induction and the occurrence of black swans. Here I introduce the
scientific perpetrators.

Recall that I have waged a war against the charlatanism of some
prominent financial economists for a long time. The points are as
follows. One Harry Markowitz received something called the Nobel
Memorial Prize in Economics (which in fact is not even a Nobel Prize as
it is granted by the Swedish central bank in honor of Alfred Nobel - it
was never in the will of the famous man). What is his achievement? By
creating an elaborate method of computing future risk if one knows
future uncertainty; in other words if markets had clearly defined rules -
which is clearly not the case. Now I explained the point to a cab driver
who laughed at the fact that someone ever thought that there was any
scientific method to understand markets and predict their attributes.
Somehow when one gets involved in financial economics, owing to the
culture of the field, one becomes likely to forget these basic facts.

CARNEADES COMES TO ROME: ON PROBABILITY AND SKEPTICISM 189

An immediate result of Dr. Markowitz’s theory was the near collapse
of the financial system in the summer of 1998 (as we saw in Chapters 1
and 5) by Long Term Capital Management (“LTCM”), a Greenwich,
Connecticut fund that had for principals two of Dr. Markowitz’s
colleagues, “Nobel” as well. They are Drs. Robert Merton (the one in
Chapter 3 trouncing Shiller) and Myron Scholes. Somehow they thought
they could scientifically “measure” their risks. They made absolutely no
allowance in the LTCM episode for the possibility of their not
understanding markets and their methods being wrong. That was not
a hypothesis to be considered. I happen to specialize in profiting from
the black swans and the breakdown of the system, and make bets
against financial economists. Suddenly I started getting some irritating
fawning respect, along with paychecks from the market. Drs. Merton
and Scholes helped put your humble author on the map and caused the
birth of your humble crisis-hunter’s firm, Empirica - as capital started
flowing to people who did the exact opposite of what they did for a
living.

One would think that when scientists make a mistake, they develop a
new science that incorporates what has been learned from it. When
academics blow up trading, one would expect them to integrate such
information in their theories and make some heroic statement to the
effect that they were wrong, but that now they have learned something
about the real world. Nothing of the sort. Instead they complain about
the behavior of their counterparts in the market who pounced on them
like vultures, thus exacerbating their downfall. Accepting what has
happened, clearly the courageous thing to do, would invalidate the ideas
they have built throughout an entire academic career. All of the
principals who engaged in a discussion of the events partook of a
masquerade of science by adducing ad hoc explanations and putting the
blame on a rare event (problem of induction: how did they know it was
a rare event?). They spent their energy defending themselves rather than
trying to make a buck with what they learned. Again compare them
with Soros who walks around telling whomever has the patience to
listen to him that he is fallible. My lesson from Soros is to start every
meeting at my trading boutique by convincing everyone that we are a
bunch of idiots who know nothing and are mistake prone, but happen
to be endowed with the rare privilege of knowing it.

190

WAX IN MY EARS

From Funeral to Funeral

I conclude with the following saddening remark about scientists in the
soft sciences. People confuse science and scientists. Science is great, but
individual scientists are dangerous. They are human; they are marred by
the biases humans have. Perhaps even more. For most scientists are hard
headed, otherwise they would not derive the patience and energy to
perform the Herculean tasks asked of them, like spending 18 hours a
day perfecting their doctoral thesis.

A scientist may be forced to act like a cheap defense lawyer rather
than a pure seeker of the truth. A doctoral thesis is “defended” by the
applicant; it would be a rare situation to see the student change his mind
upon being supplied with a convincing argument. But science is better
than scientists. It was said that science evolves from funeral to funeral.
After the LTCM collapse, a new financial economist will emerge, who
will integrate such knowledge in his science. He will be resisted by the
older ones but, again, they will be much closer to their funeral date than
he.

Montherlant’s death. Stoicism is not the stiff upper lip, hut the
illusion of victory of man against randomness. It is so easy to be
heroic. Randomness and personal elegance.

W hen the classicist aristocratic French writer Henry de Month-
erlant was told that he was about to lose his eyesight to a
degenerative disease, he found it most appropriate to take his own life.
Such is the end that becomes a classicist. Why? Because the stoic’s
prescription was precisely to elect what one can do to control one’s
destiny in front of a random outcome. At the end, one is allowed to
choose between no life at all and what one is given by destiny; we
always have an option against uncertainty. But such an attitude is not
limited to stoics; both competing sects in the ancient world, stoicism and
Epicurianism recommended such control (the difference between the
two resides in minor technicalities - neither philosophies meant then
what is commonly accepted today in middlebrow culture).

Being a hero does not necessarily mean such an extreme act as
getting killed in battle or taking one’s life - the latter is only recom-
mended in a narrow set of circumstances and considered cowardly
otherwise. Having control over randomness can be expressed in the
manner one acts in the small and the large. Recall that epic heroes

192

WAX IN MY EARS

were judged by their actions, not by the results. No matter how
sophisticated our choices, how good we are at dominating the odds,
randomness will have the last word. We are left only with dignity as a
solution - dignity defined as the execution of a protocol of behavior
that does not depend on the immediate circumstance. It may not be the
optimal one, but it certainly is the one that makes us feel best. Grace
under pressure, for example. Or in deciding not to toady up to
someone, whatever the reward. Or in fighting a duel to save face. Or in
signaling to a prospective mate during courtship: “listen, I have a crush
on you; I am obsessed with you, but I will not do a thing to
compromise my dignity. Accordingly, the slightest snub and you will
never see me again”.

This last chapter will discuss randomness from a totally new angle;
philosophical but not the hard philosophy of science and epistemology
as we saw in Part I with the black swan problem. It is a more archaic,
softer type of philosophy, the various guidelines that the ancients had
concerning the manner a man of virtue and dignity deals with
randomness - there was no real religion at the time (in the modern
sense). It is worthy of note that before the spread of what can be best
called Mediterranean monotheism, the ancients did not believe enough
in their prayers to influence the course of destiny. Their world was
dangerous, fraught with invasions and reversals of fortune. They needed
substantial prescriptions in dealing with randomness. It is such beliefs
that we will outline next.

Notes on Jackie O.’s Funeral

If a stoic were to visit us, he would feel represented by the following
poem.- To many (sophisticated) lovers of poetry, one of the greatest
poets who ever breathed is C.P. Cavafy. Cavafy was an Alexandrian
Greek civil servant with a Turkish or Arabic last name who wrote
almost a century ago in a combination of classical and modern Greek a
lean poetry that seems to have eluded the last fifteen centuries of
Western literature. Greeks treasure him like their national monument.

BACCHUS ABANDONS ANTONY

193

Most of his poems take place in Syria (his Grecosyrian poems initially
drew me to him), Asia Minor, and Alexandria. Many people believe it
worth learning formal semi-classical Greek just to savor his poems.
Somehow their acute aestheticism stripped of sentimentality provides a
relief from centuries of mawkishness in poetry and drama. He provides
a classical relief for those of us who were subjected to the middle-class
valued melodrama as represented by Dickens’s novels, romantic poetry,
and Verdi’s operas.

I was surprised to hear that Maurice Tempelsman, last consort of
Jackie Kennedy Onassis, read Cavafy’s valedictory Apoleipein o Tbeos
Antonion (The God Abandons Antony) at her funeral. The poem
addresses Marc Antony, who has just lost the battle against Octavius
and was forsaken by Bacchus the god who until then had protected him.
It is one of the most elevating poems I have ever read, beautiful because
it was the epitome of such dignified aestheticism - and because of the
gentle but edifying tone of the voice of the narrator advising a man who
had just received a crushing reversal of fortune.

The poem addresses Antony, now defeated and betrayed (according
to legend, even his horse deserted him to go to his enemy Octavius). It
asks him to just bid her farewell, Alexandria the city that is leaving him.
It tells him not to mourn his luck, not to enter denial, not to believe that
his ears and eyes are deceiving him. Antony, do not degrade yourself
with empty hopes. Antony,

Just listen while shaken by emotion but not with the coward’s

imploration and complaints.

While shaken with emotion. No stiff upper lip. There is nothing wrong
and undignified with emotions - we are cut to have them. What is
wrong is not following the heroic, or at least, the dignified path. That is
what stoicism truly means. It is the attempt by man to get even with
probability. I need not be nasty at all and break the spell of the poem
and its message, but I cannot resist some cynicism. A couple of decades
later, Cavafy, while dying of throat cancer did not quite follow the
prescription. Deprived of his voice by the surgeons, he used to randomly
enter undignified spells of crying and cling to his visitors, preventing
them from leaving his death room.

194

WAX IN MY EARS

Some history. I said that stoicism has rather little to do with the stiff
upper lip notion that we believe it means. Started as an intellectual
movement in antiquity by a Phoenician Cypriot, Zeno of Kitium, it
developed by Roman time into a life based on a system of virtues - in the
ancient sense when virtue meant virtu, the sort of belief in which virtue
is its own reward. There developed a social model for a stoic person, like
the gentlemen in Victorian England. Its tenets can thus be summarized
as follows: the stoic is a person who combines the qualities of wisdom,
upright dealing, and courage. The stoic will thus be immune from life’s
gyrations as he will be superior to the wounds from some of life’s dirty
tricks. But things can be carried to the extreme; the stern Cato found it
beneath him to have human feelings. A more human version can be read
in Seneca’s Letters From a Stoic, a soothing and surprisingly readable
book that I distribute to my trader friends (Seneca also took his own life
when cornered by destiny).

Randomness and Personal Elegance

The reader knows my opinion on unsolicited advice and sermons on how
to behave in life. Recall that ideas do not truly sink in when emotions
come into play; we do not use our rational brain outside of classrooms.
Self-help books (even when they are not written by charlatans) are
largely ineffectual. Good, enlightened (and “friendly”) advice and
eloquent sermons, do not register for more than a few moments when
they go against our wiring. The interesting thing about stoicism is that it
plays on dignity and personal aesthetics, which are part of our genes.
Start stressing personal elegance at your next misfortune. Exhibit sapere
vivere (“know how to live”) in all circumstances.

Dress at your best on your execution day (shave carefully); try to
leave a good impression on the death squad by standing erect and
proud. Try not to play victim when diagnosed with cancer (hide it from
others and only share the information with the doctor - it will avert the
platitudes and nobody will treat you like a victim worthy of their pity; in
addition the dignified attitude will make both defeat and victory feel

BACCHUS ABANDONS ANTONY

195

equally heroic). Be extremely courteous to your assistant when you lose
money (instead of taking it out on him as many of the traders whom I
scorn routinely do). Try not to blame others for your fate, even if they
deserve blame. Never exhibit any self pity, even if your significant other
bolts with the handsome ski instructor or the younger aspiring model.
Do not complain. If you suffer from a benign version of the “attitude
problem”, like my childhood friend Camille Abousleiman, do not start
playing nice guy if your business dries up (he sent a heroic e-mail to his
colleagues informing them “less business, but same attitude”). The only
article Lady Fortuna has no control over is your behavior. Good luck.

BEWARE THE LONDON TRAFFIC JAMS

A couple of years after we left him looking at John smoking a cigarette
with a modicum of schadenfreude, Nero’s skepticism ended up
paying off. Simultaneously as he beat the 28% odds, up to the point of
complete cure, he made a series of exhilarating personal and professional
victories. Not only did he end up sampling the next level of wealth but he
got the riches right when other Wall Street hot shots got poor, which could
have allowed him to buy the goods they owned at very large discounts, if
he wanted to. But he acquired very little, and certainly none of the goods
Wall Streeters usually buy. But Nero did engage in occasional excess.

Friday afternoon traffic in London can be dreadful. Nero started
spending more time there. He developed an obsession with traffic jams.
One day he spent five hours moving West from his office in the City of
London towards a cottage in the Cotswolds where he stayed most
weekends. The frustration prompted Nero to get a helicopter flying
license, through a crash course in Cambridgeshire. He realized that the
train was probably an easier solution to get out of town for the
weekend, but he felt the urge for a pet extravagance. The other result of
his frustration was his no less dangerous commuting on a bicycle
between his flat in Kensington and his office in the City.

Nero’s excessive probability consciousness in his profession somehow
did not register fully into his treatment of physical risk. For Nero’s
helicopter crashed as he was landing it near Battersea Park on a windy
day. He was alone in it. In the end the black swan got its man.

1. This is the Dry den translation of Plutarch’s Lives.

2. For an example of pseudoscientific historicism, I suggest Francis
Fukuyama, 1992, The End of History and the Last Man, New York:
Free Press.

3. Richard Dawkins, 1990 (1970), The Selfish Gene, 2nd ed., Oxford:
Oxford University Press.

4. Alan Sokal, 1996, Transgressing the Boundaries: Toward a
Transformative Hermeneutics of Quantum Gravity, Social Text
(spring-summer).

5. www.monash.edu.au

6. Brian Magee, 1997, Confessions of a Philosopher, London: Weidenfeld
& Nicolson.

7. Malachi Haim Hacohen, 2001, Karl Popper, The Formative Years,
1902-1945: Politics and Philosophy in Interwar Vienna, New York:
Cambridge University Press.

8. R. Sullivan, A. Timmerman and H. White, 1999, Data-Snooping,
Technical Trading Rule Performance and the Bookstrap, Journal of
Finance, October.

9. I thank my correspondent Francesco Corielli from Bocconi for his
remark on meta-analysis.

10. Deborah J. Bennett, 1998, Randomness, Cambridge, MA: Harvard
University Press.

11. Antonio Damasio, 1995, Descartes’ Error: Emotion, Reason, and the
Human Brain, New York: Avon Books. See also Joseph Ledoux, 1998,
The Emotional Brain: The Mysterious Underpinning of Emotional
Life, New York: Touchstone Books.

12. Jean-Manuel Rozan, 1999, Le fric, Paris: Michel Lafon.

Abelson, Alan 54

Abousleiman, Camille 195

absurdity 156-7

Academy 183

accumulators 120-3

Achilles M. 130

adaptation 98

Adams, Evelyn 133

adverse selection 132

aesthetics 64-7

age 51-2, 55-6

Alexander the Great 35

alternative histories 26-9

alternative medicine 137-9

alternative sample paths 41-3

anger, managing 172-3

anonymous letter scam 131

Antony, Marc 143, 193

artificial thinking 62 -4

Asian currencies 93

Arthur, Brian 145, 146

artificial random data generators 140

Asia Minor 50

asset price inflation 122-3

astrology 106-7

asymmetry 84-98, 102

Australia 102

averaging down 72

Babbage, Nigel 186
backtesting 134-6
Bacon, Francis 100
bearishness 86-93

behavior 22-3, 152-8
Skinner’s pigeon experiment 178-9
behavioral finance and economics 157
beliefs

overestimation of accuracy in 79
path dependence and 186-8
Bell Curve 86
Berra, Yogi 10, 106
Bergson, Henri 173-4
biases

survivorship 80, 117-41
in understanding probability
158-60
biology 158
birthday paradox 132
black swan problem 10, 28, 100, 102
Bloomberg machine 164-6
blow up 15, 49, 77
risk of 20-1

bond market crash of 1994 15, 130

book reviews 134

Brady bonds 69

brain 158

Breton, Andre 65

Buffett, Warren 121

Bulha, Andrew C. 62

bull market 122-3

bullishness 86-93

Buridan, Jean 148

Buridan’s donkey 147-8

business orientation 30

Caesar, Julius 35, 143

INDEX

199

call options 160
cancer clusters 140
cancer cures 137-9
Canova, Antonio 126
Carlos (emerging markets trader)
68-74

Carneades of Cyrene 183-4
Catholic church 66
Cato 183, 194
causality 165-6, 175-9
Cavafy, C.P. 56, 192-3
chaos theory 143
charlatanism 4, 131, 133, 137-9
chess expertise 31

Chicago Mercantile Exchange 11, 13
chief strategists 88
Cicero 185

cigarette smoking 181
Claudel, Paul 105
Cleopatra 143
CNBC 163
coincidences 131-41
company earnings 136-7
competence 128-9
complexity theory 147
compounding effect 156
computational finance 76
computers 46
reverse Turing test 62-3
Comte, Auguste 107
conditional life expectancy 164
conditional probabilities 155
confidence levels 166, 168
confusion, table of 2-4
Constantinople 50
continuity 82
contrarians 152
control

over destiny 191-2
self-control 179-81
correctness and intelligibility 37-8
counterintuitive truths 34-9
Credit Suisse First Boston 175
criminal trials 154—6
crisis hunters 96
critical thinking 4, 185
absence of 80
Croesus 9, 10

cross-sectional problem 74
Cyrene 183
Cyrus, King 10

Dada Engine 62-3
Darwinism 81-2
data mining 133
data snooping 135-6
Dawkins, Richard 62, 81
Debreu, Gerard 147
deductive statements 61
demarcation, problem of 107
denial 80

denigration of history 28, 47-8
Diaconis, Percy 133
dialecticians 183-4
dignity 192
dip buyers 71, 80
discussion meeting 86-7
distilled thinking 51-6
distribution of the maximum of
random variables 163
Dos Passos, John 134
Drosnin, Michael 133

econometrics 92, 97-8
economic analysis 79
economics

behavioral finance and economics
157

mathematical modeling and 146-7

normative science 157-8
efficient markets 54
Einstein, Albert 38, 45
elegance, personal 194-5
Eluard, Paul 65

emerging market bonds trading 68-74

emotions 161-2, 172-3

Empirica 189

empiricism 100, 101

encounters, random 132-3

environment 153—4

environment mapping 158

envy 19-21

epic poets 35

Epicurianism 191

epistemology 100

ergodicity 50-1, 129-31

200

INDEX

evidence 154-6

absence of evidence and evidence of
absence 162
evolution 46-7
naive theories 81-3
evolutionary psychology 158
expectation 150
of the maximum 128-9
and median 84-6
Exquisite Cadavers 65

falsificationism 106-8
fame 144

Feynman, Richard 47
filtering methods 166-7
financial economists 105-6, 188-9
experts on television 162-4
financial engineering 98
firehouse effect 73
fitness 55, 81-3
flow 161

forecast and prophecy 36
France 185

gamblers’ ticks 176-8
Gates, Bill 145
gerontocracy 55-6
global warming 91
God 109
Gorgias 184

Gould, Steven Jay 81, 84-5
grammar 44
recursive grammar 62-3
Grant, Jim 54 ,

Greek Orthodox church 66
Greene, Graham 27-8, 174

habitat, natural 153-4
Flannibal 35

Hayek, Friedrich von 108
hedge funds 54, 71, 189
Flegel, George W.F. 64
heroes 35, 153, 191-2
high-yield bonds trading 17-21, 74—8
historical determinism 49
history 35, 93
alternative histories 26-9
denigration of 28, 47-8

financial engineering and 98
mathematics and 40-59
Hitler, Adolf 35
Homeric heroes 153
Hume, David 100

Iliad 35

independence 146

induction, problem of 10, 28, 99-110
inductive statements 61
information 154
and increase of knowledge 107
news 51-3, 54, 59
and noise 51-3, 56-9
intelligibility and correctness 37-8
interest rate differential 75, 76
International Monetary Fund 74
introspection 29-30, 40-59
inverse rare events 96
investment categories, selection of
137

investment houses 13-14
discussion meeting 86-7
investment managers 127-31

Jean-Patrice 33-4

John (high-yield trader) 17-21, 74-8
joint probability 155-6
journalism 35-6, 51, 54-5, 162-4

Kafka, Franz 156
Kahneman, Daniel 20, 48, 157-8
Kaletsky, Anatole 54
Kenny 32-3

Keynes, John Maynard 45, 107
knowledge 107
Korax 184

language 65-6
see also grammar
learning from mistakes 48-9, 189
Leibniz, Gottfried 82
leverage 76, 77
life expectancy 163-4
linear combination 150
Linnaeus, Carl 82
literary intellectuals 60-4
long-haul investment 79

INDEX

201

Long Term Capital Management
(LTCM) 54, 71, 189
long volatility positions 161
Louie (veteran trader) 74
Lourdes 139

loyalty to ideas/beliefs 79, 186-8
Lucas, Robert 98
Lucas critique 98
lucky fool (definition) 1

macro traders 79
Magee, Brian 109
Marc (city lawyer) 117-20
markets, volatility of 53-4
Markowitz, Harry 188-9
Marxism 98
mathematics 28
and history 40-59
and nonlinearity 146-8
see also Monte Carlo methods;
probability
MBAs 31, 37
mean 84-6

media 35-6, 162-4, 173-4
see also journalism
median 84-6
medical journalists 162
medicine 84-5, 136, 158
alternative medicine 137-9
meltdown of summer 1998 71-4, 76,
189

Merton, Robert C. 54, 189
methodology 101-2
Mexico 93, 94-5
Microsoft 145
Mill, John Stuart 100
Millionaire Next Door, The 120-3
mistakes, learning from 48-9, 189
momentum players 152
Monod, Jacques 81
monotheism 184
Monte Carlo methods
creating artificial history 40-8
generation of text 62-3
investment managers’ performance
127-31

Montherlant, Henry de 191
Mosteller, Frederick 133

multivariate analysis 165-6

naive empiricism 101
naive evolutionary theories 81-3
natural habitat 153-4
negative mutations 81
neoclassical economics 157
neurobiology 158-9
‘new novels’ 47
news 51-3, 54, 59
Newtonian physics 106-7
Niederhoffer, Victor 100-3
noise 165-7
filtering methods 166-7
ignoring 180-1
and information 51-3, 56-9
and meaning 2
nonlinearities 142-8
non-randomness, test of 139-40
normative sciences 157-8

O.J. Simpson trial 154-6
O’Connell, Marty 73
Odyssey 171
Omega TradeStation 136
Onassis, Jackie Kennedy 193
one-dimensional spaces 156
open society 108
options 90, 102, 160-1
out-of-the-money options 102, 160
outcomes, possible 24-5
outliers 91

Pascal’s wager 109-10
path dependence 144-6
beliefs 186-8
Patrocles 35
Pauling, Linus 138
Pearson, Karl 139-40
pecking order 18-21, 22-3, 119-20
peer relations 29-34
perfect noise 165
performance

hormones and signaling 22-3, 83
track record 126, 127-31
personal elegance 194-5
Pesaran, Hashem 97
peso problem 93, 94-5

202

INDEX

philosophy 12-13, 45, 64
of science 3, 99-110
stoicism 191-5
Philostratus 56
physicists 31-2
physics 106-7
Pi 43-4

pigeon experiment 178-9
planning, lack of 80
poetry 2, 64-7
Polya process 146
Popper, Karl 61, 103-9
population size 124, 130
portfolios 94

positions, loyalty to 79, 187
positive sciences 158
positivism 107-8
possible outcomes, range of 24-5
premium buyers/sellers 161
probability 2, 37
blindness 149-68
child of skepticism 184-5
introspection 40-59
and speculation 182-90
prophecy and forecast 36
proprietary trading 14-17
Proust, Marcel 153
In Search of Time Lost 19, 185-6
pseudothinkers 64
psychology 152-8
Pyrrho 179-80

quants 44, 75-6
QWERTY keyboard 144-5

R-, Lauren 30
Rabin, Itzhak 133

random sample paths (random runs)
42-3

randomness fool, traits of 78-80
rare events 89-90, 91
case studies 68-78
evolution and 82-3
fallacy 93-8

non-detection by statisticians 96
rationality 98

and biases in understanding
probability 158-62

reality 28-9

recursive grammar 62-3
reference case problem 139—40
regime switching 55, 82-
religion 66

reverse Turing test 62-3
rhetoricians 184
rich people 120-3
Rimbaud, Arthur 2
risk 33-4
aversion 15-16
of blow up 20-1
risk managers 38-9
risk measurers 188-9
Robbe-Grillet, Alain 47
Robertson, Julian 79
‘Robin Hood’ investment policy 124
Rogers, Jim 90
Roman Senate 183
Rozan, Jean-Manuel 186
Russian bonds 71-4
Russian roulette 27-8
Russian ruble 95
Russian scientists 31-2

Sagan, Carl 139

sample paths 41-3

Samuelson, Paul 147

sandpile effect 142-6

Santa Fe Institute 147

scaling property of randomness 57-9

Schadenfreude 21-2

Scholes, Myron 189

science 2, 5

philosophy of science 3, 99-110
positive and normative 157-8
and scientists 190
survivorship biases 140-1
symmetry and 90-3
scientific intellectuals 60-4
scientism 98
scientists 5, 190

risk measurers and meltdown of
1998 188-9
in trading 29-32
self-contradiction 185-8
self-control 179-81
Senate, Roman 183

INDEX

203

Seneca 194
serotonin 22-3, 83
Shiller, Robert 35-6, 53-4
shorting 70

signal and noise 166-7, 180-1
signaling, hormones and 22-3, 83
Simpson (O.J.) trial 154-6
sirens, the 171
skepticism 183-5
skewness 10, 84-98, 146
Skinner, B.F. 178-9
smoothing kernel 166-7
Socrates 183
Sokal, Alan 61, 62
Solon 9

Soros, George 80, 90, 103-4, 109,

128, 189

self-contradiction 186-7
spontaneous remission 138-9
stationarity, problem of 97-8
statistical arbitrageurs 100-1
statistics 96-8, 107, 109-10
Stix, Gary 54
stochastic processes 42
stock market crash of 1987 90
stoicism 191-5
stop losses 80, 110
student movement, France 1968 185
summing under histories 47
superstition 1, 176-8
survival 55-6
of the least fit 68-83
survivorship bias 80, 117-41
symbolism 2
symmetry 90-3
see also asymmetry

Taleb, Nassim Nicholas
ancestry 50
bosses 32-4

comparison with Niederhoffer 102-3
development of gamblers’ ticks
175-7

discovery of Popper 104—6
discussion meetings 87

peer relations 31-2
and voicing market calls 88-9
television 163-4, 173-4
Tempelsman, Maurice 193
testable statements 101-2
time series 91-3, 97
track record 126, 127-31
traders/trading 4
appearance and intellect 70
body language 23
bosses 32-4

emerging market bonds 68-74
high-yield bonds 17-21, 74-8
macro traders 79
Monte Carlo model 46-7
proprietary trading 14-17
scientists 29-32
trading rules 134-6
trading strategies 152
traits of randomness fools 78-80
Treasury bonds 16, 94
trials, criminal 154-6
Tulip, Nero 11-17, 21-2, 150-1, 196
Turing test, reverse 62-3
Tversky, Amos 20, 48, 157-8

unabomber 40-1
unconditional probabilities 155

Valery, Paul 2

verification 106-8

Vienna Circle 60-1, 66, 107, 109

vitamin C 138

volatility of markets 53-4

Wall Street Journal 53
Walras, Leon 147
Will, George 35-6
Wilmott, Paul 134
work ethics 16-17, 105

yield hogs see hedge funds

Zeno of Kitium 194
Zorglubs 46